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Electrical Engineering and Computer Science

EECS Courses

Number Title
101 New Student Seminar
137 Visual Basic for Engineers
138 Introduction to Computing
140 Introduction to Digital Logic Design
141 Introduction to Digital Logic Design. Honors
168 Programming I
169 Programming I - Honors
210 Discrete Structures
211 Circuits I
212 Circuits II
220 Electromagnetics I
221 Electromagnetics I
268 Programming II
312 Electronic Circuits I
315 Electric Circuits and Machines
316 Circuits, Electronics and Instrumentation
317 Electronics and Instrumentation
318 Circuits and Electronics Lab
360 Signal and System Analysis
368 Programming Language Paradigms
388 Embedded Systems
399 Projects
412 Electronic Circuits II
420 Electromagnetics II
441 Power Systems Engineering II
443 Digital Systems Design
444 Control Systems
448 Software Engineering I
461 Probability and Statistics
470 Electronic Devices and Properties of Materials
498 Honors Research
501 Senior Design Laboratory I
502 Senior Design Laboratory II
510 Introduction to the Theory of Computing
512 Electronic Circuits III
541 Computer Systems Design Laboratory I
542 Computer Systems Design Laboratory II
547 Power System Analysis I
560 Data Structures
562 Introduction to Communication Systems
563 Introduction to Communication Networks
565 Introduction to Information and Computer Security
581 Computer Science Design I
582 Computer Science Design II
611 Electromagnetic Compatibility
622 Microwave and Radio Transmission Systems
628 Fiber Optic Communication Systems
638 Fundamentals of Expert Systems
639 Introduction to Scientific Computing
644 Introduction to Digital Signal Processing
645 Computer Architecture
647 Introduction to Database Systems
649 Introduction to Artificial Intelligence
660 Fundamentals of Computer Algorithms
662 Programming Languages
664 Introduction to Digital Communication Systems
665 Compiler Construction
670 Introduction to Semiconductor Processing
672 Introduction to Computer Graphics
678 Introduction to Operating Systems
690 Special Topics
692 Directed Reading
700 Special Topics
711 Security Management and Audit
713 High-Speed Digital Circuit Design
718 Graph Algorithms
721 Antennas
723 Microwave Engineering
725 Introduction to Radar Systems
728 Fiber-optic measurement and sensors
730 Introduction to Bioinformatics
731 Introduction to Data Science
738 Machine Learning
739 Parallel Scientific Computing
740 Digital Image Processing
741 Computer Vision
742 Static Analysis
743 Advanced Computer Architecture
744 Communications and Radar Digital Signal Processing
745 Implementation of Networks
750 Advanced Operating Systems
753 Embedded and Real Time Computer Systems
755 Software Modeling and Analysis
759 Estimation and Control of Unmanned Autonomous Systems
762 Programming Language Foundation I
764 Analysis of Algorithms
765 Introduction to Cryptography and Computer Security
767 Information Retrieval
768 Virtual Machines
769 Information Theory
773 Advanced Graphics
774 Geometric Modeling
775 Visualization
776 Functional Programming and Domain Specific Languages
780 Communication Networks
781 Numerical Analysis I
782 Numerical Analysis II
784 Science of Communication Networks
786 Digital VLSI (Very-Large-Scale Integration)
788 Analog Integrated Circuit Design
800 Special Topics
801 Directed Graduate Readings
802 EECS Colloquium and Seminar on Professional Issues
812 Software Requirements Engineering
820 Advanced Electromagnetics
823 Microwave Remote Sensing
828 Advanced Fiber-Optic Communications
830 Advanced Artificial Intelligence
831 Introduction to Systems Biology
837 Data Mining
838 Applications of Machine Learning in Bioinformatics
839 Mining Special Data
843 Programming Language Foundation II
844 Adaptive Signal Processing
861 Random Signals and Noise
862 Principles of Digital Communication Systems
863 Network Analysis, Simulation, and Measurements
865 Wireless Communication Systems
866 Network Security
868 Mathematical Optimization with Applications
869 Error Control Coding
881 High-Performance Networking
882 Mobile Wireless Networking
888 Internet Routing Architectures
891 Graduate Problems
899 Master’s Thesis
900 Seminar
940 Theoretic Foundation of Data Science
965 Detection and Estimation Theory
983 Resilient and Survivable Networking
998 Post-Master’s Research
999 Doctoral Dissertation

To view the course description for a given EECS course select it from the list to the left.

EECS 101 - New Student Seminar

1 credit hours

A seminar intended to help connect freshmen and transfer EECS students to the EECS department, their chosen profession, and each other. Topics include overviews of the various disciplines, curricula and advising, ethics and professionalism, student organizations and extracurricular activities, senior projects, and career planning.

Prerequisite(s): None

EECS 137 - Visual Basic for Engineers

3 credit hours

Introduction of computer-based problem solving techniques for engineering practice with emphasis on good programming practices and the integration of appropriate computational and related tools. Solutions are computed using Visual Basic, specifically VBA within Excel. Elementary numerical and statistical methods are applied to the solution of sets of linear and nonlinear algebraic equations, linear regression, and root finding. Microsoft Office is used with the computational tools to provide integrated report generation capability. Two lectures and a weekly laboratory instruction.

Prerequisite(s): Math 104

EECS 138 - Introduction to Computing

3 credit hours

Algorithm development, basic computer organization, syntax and semantics of a high-level programming language, including testing and debugging. Concept of structure in data and programs, arrays, top-down design, subroutines and library programs. Abstract data types. System concepts such as compilation and files. Nature and scope of computer science.

Prerequisite(s): MATH 101 or MATH 104, or meeting the requirements to enroll in MATH 115 or MATH 121 or MATH 125 or MATH 145.

EECS 140 - Introduction to Digital Logic Design

4 credit hours

An introductory course in digital logic circuits covering number representation, digital codes, Boolean Algebra, combinatorial logic design, sequential logic design, and programmable logic devices.

Prerequisite(s): Corequisite: MATH 104

EECS 141 - Introduction to Digital Logic Design. Honors

4 credit hours

An introductory course in digital logic circuits covering number representation, digital codes, Boolean algebra, combinatorial logic design, sequential logic design, and programmable logic devices. This course is intended for highly motivated students and includes honors-level assignments.

Prerequisite(s): Prerequisite: Co-requisite: MATH 121, or MATH 125 or MATH 145, plus either acceptance into the KU Honors Program or consent of instructor.

EECS 168 - Programming I

4 credit hours

Problem solving using a high level programming language and object oriented software design. Fundamental stages of software development are discussed: problem specification, program design, implementation, testing, and documentation. Introduction to programming using an object oriented language: using classes, defining classes, and extending classes. Introduction to algorithms and data structures useful for problem solving: arrays, lists, files, searching, and sorting. Student will be responsible for designing, implementing, testing, and documenting independent programming projects. Professional ethics are defined and discussed in particular with respect to computer rights and responsibilities.

Prerequisite(s): Corequisite: MATH 104

EECS 169 - Programming I - Honors

4 credit hours

Problem solving using a high level programming language and object oriented software design. Fundamental stages of software development are discussed: problem specification, program design, implementation, testing, and documentation. Introduction to programming using an object oriented language: using classes, defining classes, extending classes. Introduction to algorithms and data structures useful for problem solving: arrays, lists, files, searching, and sorting. Students will be responsible for designing, implementing, testing, and documenting independent programming projects. Professional ethics are defined and discussed in particular with respect to computer rights and responsibilities. This course is intended for highly motivated students and includes honors-level assignments.

Prerequisite(s): Corequisite: MATH 121 or MATH 125 or MATH 145, plus either acceptance into the KU Honors Program or consent of instructor.

EECS 210 - Discrete Structures

4 credit hours

Mathematical foundations including logic, sets and functions, general proof techniques, mathematical induction, sequences and summations, number theory, basic and advanced counting techniques, solution of recurrence relations, equivalence relations, partial order relations, lattices, graphs and trees, algorithmic complexity, and algorithm design and analysis. Throughout there will be an emphasis on the development of general problem solving skills including algorithmic specification of solutions and the use of discrete structures in a variety of applications.

Prerequisite(s): EECS 168 or 169 (or equivalent) and MATH 122 or MATH 126 or MATH 146

EECS 211 - Circuits I

3 credit hours

Analysis of linear electrical circuits: Kirchoff's laws; source, resistor, capacitor and inductor models; nodal and mesh analysis; network theorems; transient analysis; Laplace transform analysis; steady-state sinusoidal analysis; computer-aided analysis.

Prerequisite(s): Corequisites: Math 220 and Math 290

EECS 212 - Circuits II

4 credit hours

Continued study of electrical circuits: Steady state power analysis, three-phase circuits, transformers, frequency response, two-port network analysis.

Prerequisite(s): EECS 211

EECS 220 - Electromagnetics I

4 credit hours

Vector analysis. Electrostatic and magnetostatic fields in a vacuum and material media. Electromagnetic fields and Maxwell's equations for time-varying sources. The relationship between field and circuit theory. Simple applications of Maxwell's equations.

Prerequisite(s): MATH 220, MATH 290, PHSX 211 and EECS 211

EECS 221 - Electromagnetics I

3 credit hours

Electrostatic and magnetostatic fields in a vacuum and material media. Electromagnetic fields and Maxwell's equations for time-varying sources. The relationship between field and circuit theory. Simple applications of Maxwell's equations.

Prerequisite(s): MATH 127, MATH 220, EECS 211, and either PHSX 210 or PHSX 211.

EECS 268 - Programming II

4 credit hours

This course continues developing problem solving techniques by focusing on the imperative and object-oriented styles using Abstract Data Types. Basic data structures such as stacks, queues, and trees will be covered. Recursion. Basic notions of algorithmic efficiency and performance analysis in the context of sorting algorithms. Basic Object-Oriented techniques. An associated laboratory will develop projects reinforcing the lecture material. Three class periods and one laboratory period per week.

Prerequisite(s): EECS 168 or EECS 169

EECS 312 - Electronic Circuits I

3 credit hours

Introduction to diodes, BJT’s and MOSFET’s and their use in electronic circuits, especially digital circuits.

Prerequisite(s): Upper-level EECS eligibility. Corequisite: EECS 212

EECS 315 - Electric Circuits and Machines

3 credit hours

Introduction to DC and AC electrical circuit analysis techniques, AC power calculations, transformers, three-phase systems, magnetic circuits, and DC and AC machines with a focus on applications. Not open to electrical or computer engineering majors.

Prerequisite(s): A course in differential equations and eight hours of physics.

EECS 316 - Circuits, Electronics and Instrumentation

3 credit hours

Introduction to DC and AC electrical circuit analysis, operational amplifiers, semiconductors, digital circuits and systems, and electronic instrumentation and measurements with a focus on applications. Not open to electrical or computer engineering majors. Students may not receive credit for both EECS 316 and EECS 317.

Prerequisite(s): A course in differential equations and eight hours of physics.

EECS 317 - Electronics and Instrumentation

2 credit hours

Introduction to operational amplifiers, semiconductors, digital circuits and systems, and electronic instrumentation and measurements with a focus on applications. Not open to electrical or computer engineering majors. Students may not receive credit for both EECS 316 and EECS 317.

Prerequisite(s): EECS 315

EECS 318 - Circuits and Electronics Lab

1 credit hours

Laboratory exercises intended to complement EECS 316 and EECS 317. Experiments include DC circuits, analog electronics, and digital electronics. Not open to electrical or computer engineering majors.

Prerequisite(s): Corequisite: EECS 316 or EECS 317

EECS 360 - Signal and System Analysis

4 credit hours

Fourier signal analysis (series and transform); linear system analysis (continuous and discrete); Z-transforms; analog and digital filter analysis. Analysis and design of continuous and discrete time systems using MATLAB.

Prerequisite(s): Prerequisite: Upper-level EECS eligibility,and EECS 212.

EECS 368 - Programming Language Paradigms

3 credit hours

The course is a survey of programming languages: their attributes, uses, advantages, and disadvantages. Topics include scopes, parameter passing, storage management, control flow, exception handling, encapsulation and modularization mechanism, reusability through genericity and inheritance, and type systems. In particular, several different languages will be studied which exemplify different language philosophies (e.g., procedural, functional, object-oriented, logic, scripting).

Prerequisite(s): EECS 268 and upper-level EECS eligibility

EECS 388 - Embedded Systems

4 credit hours

This course will address internal organization of micro-controller systems, sometimes called embedded systems, used in a wide variety of engineered systems: programming in C and assembly language; input and output systems; collecting data from sensors; and controlling external devices. This course will focus on one or two specific microprocessors, software development and organization, and building embedded systems.

Prerequisite(s): EECS 140 or EECS 141, and EECS 168 or EECS 169, and upper-level EECS elegibility

EECS 399 - Projects

1-5 credit hours

An electrical engineering, computer engineering, or computer science project pursued under the student’s initiative, culminating in a comprehensive report, with special emphasis on orderly preparation and effective composition.

Prerequisite(s): Upper-level EECS eligibility and consent of instructor

EECS 412 - Electronic Circuits II

4 credit hours

Discrete and integrated amplifier analysis and design. Introduction to feedback amplifier analysis and design. Introduction to feedback amplifiers

Prerequisite(s): EECS 312 and upper-level EECS eligibility

EECS 420 - Electromagnetics II

4 credit hours

This course applies electromagnetic analysis to high frequency devices and systems where wave propagation effects cannot be neglected. Topics covered include transmission lines, space waves, waveguides, radiation, and antennas. Laboratory experiments include transmission line, waveguide, and antenna measurements and characterizations. 3 hours lecture, 1 hour laboratory.

Prerequisite(s): EECS 220 and upper-level EECS eligibility

EECS 441 - Power Systems Engineering II

3 credit hours

A continuation of ARCE 640 that integrates system components into functional, safe, and reliable power distribution systems for commercial, industrial and institutional (CII) facilities. Service entrance design, distribution system layout and reliability, emergency and standby power system design, medium-voltage distribution systems, symmetrical fault analysis, and special equipment and occupancies. (Same as ARCE 641.)

Prerequisite(s): Either ARCE 640 or EECS 212, and Upper-Level EECS Eligibility.

EECS 443 - Digital Systems Design

4 credit hours

The design of digital systems from hardware point of view. The implementation of combinational and sequential circuits. Introduction to VHDL, and its use in modeling and designing digital systems.

Prerequisite(s): EECS 388

EECS 444 - Control Systems

3 credit hours

An introduction to the modeling, analysis, and design of linear control systems. Topics include mathematical models, feedback concepts, state-space methods, time response, system stability in the time and transform domains, design using PID control and series compensation, and digital controller implementation.

Prerequisite(s): EECS 212 and EECS 360

EECS 448 - Software Engineering I

4 credit hours

This course is an introduction to software engineering, and it covers the systematic development of software products. It outlines the scope of software engineering, including life-cycle models, software process, teams, tools, testing, planning, and estimating. It concentrates on requirements, analysis, design, implementation, and maintenance of software products. The laboratory covers CASE tools, configuration control tools, UML diagrams, integrated development environments, and project specific components.

Prerequisite(s): EECS 268 and upper-level EECS eligibility

EECS 461 - Probability and Statistics

3 credit hours

Introduction to probability and statistics with applications. Reliability of systems. Discrete and continuous random variables. Expectations, functions of random variables, and linear regression. Sampling distributions, confidence intervals, and hypothesis testing. Joint, marginal, and conditional distribution and densities

Prerequisite(s): MATH 290, MATH 220, and upper-level EECS eligibility.

EECS 470 - Electronic Devices and Properties of Materials

3 credit hours

An introduction to crystal structures, and metal, insulator, and semiconductor properties. Topics covered include the thermal, electric, dielectric, and optical properties of these materials. A significant portion of this course is devoted to the properties of semiconductors and semiconductor devices.

Prerequisite(s): PHSX 313 and upper-level EECS eligibility

EECS 498 - Honors Research

1-2 credit hours

Arranged to allow students to satisfy the independent research requirement for graduation with departmental honors.

Prerequisite(s): Consent of instructor and upper-level EECS eligibility

EECS 501 - Senior Design Laboratory I

3 credit hours

A lecture/laboratory course involving the design and implementation of prototypes of electrical and computer type products and systems. The project specifications require consideration of ethics, economics, manufacturing, and safety.

Prerequisite(s): EECS 412

EECS 502 - Senior Design Laboratory II

3 credit hours

A lecture/laboratory course involving the design and implementation of prototypes of electrical and computer type products and systems. The project specifications require consideration of ethics, economics, health, manufacturing, and safety.

Prerequisite(s): EECS 501

EECS 510 - Introduction to the Theory of Computing

3 credit hours

Finite state automata and regular expressions. Context-free grammars and pushdown automata. Turing machines. Models of computable functions and undecidable problems. The course emphasis is on the theory of computability, especially on showing limits of computation. May be taken for graduate credit. (Same as MATH 510.)

Prerequisite(s): EECS 210 and upper-level EECS eligibility

EECS 512 - Electronic Circuits III

3 credit hours

Feedback amplifier circuit analysis, power amplifiers, analog IC op-amp techniques and analysis, filter approximation and realization, oscillators, wave generators and shapers.

Prerequisite(s): EECS 412

EECS 541 - Computer Systems Design Laboratory I

3 credit hours

A two semester lecture/laboratory course involving the specification, design, implementation, analysis, and documentation of a significant hardware and software computer system. Laboratory work involves software, hardware, and hardware/software trade-offs. Project requirements include consideration of ethics, economics, manufacturing, safety, and health aspects of product development. Can be taken only during the senior year.

Prerequisite(s): EECS 443 and EECS 448

EECS 542 - Computer Systems Design Laboratory II

3 credit hours

A two semester lecture/laboratory course involving the specification, design, implementation, analysis, and documentation of a significant hardware and software computer system. Laboratory work involves software, hardware, and hardware/software trade-offs. Project requirements include consideration of ethics, economics, manufacturing, safety, and health aspects of product development. Can be taken only during the senior year.

Prerequisite(s): EECS 541

EECS 547 - Power System Analysis I

3 credit hours

Introduction to the analysis of commercial, industrial, and utility power systems. Emphasis is placed on modeling system components which include transmission and distribution lines, transformers, induction machines, and synchronous machines and the development of a power system model for analysis from these components. System modeling will be applied to short-circuit studies and used to analyze symmetrical faults, to develop sequence networks using symmetrical components, and analyze unsymmetrical faults. (Same as ARCE 647.)

Prerequisite(s): Either ARCE 640 or EECS 212, and Upper-Level EECS Eligibility.

EECS 560 - Data Structures

4 credit hours

Data abstraction and abstract data types. Topics include the design and implementation of dictionary, priority queues, concatenated queue, disjoint set structures, graphs, and other advanced data structures based on balanced and unbalanced tree structures. Special emphasis will be placed on the implementations of these structures and their performance tradeoffs. Both asymptotic complexity analysis and experimental profiling techniques will be introduced. Labs will be used to provide students with hands-on experience in the implementations of various abstract data types and to perform experimental performance analysis.

Prerequisite(s): EECS 210 and EECS 448

EECS 562 - Introduction to Communication Systems

4 credit hours

A first course in communications, including lectures and integrated laboratory experiments. After a review of spectral analysis and signal transmission, analog and digital communications are studied. Topics include: sampling, pulse amplitude modulation, and pulse code modulation; analog and digital amplitude, frequency, and phase modulation; frequency and time division multiplexing; and noise performance of analog modulation techniques.

Prerequisite(s): EECS 212 and EECS 360

EECS 563 - Introduction to Communication Networks

3 credit hours

An introduction to the principles used in communication networks is given in this course. Topics include a discussion of the uses of communications networks, network traffic, network impairments, standards, layered reference models for organizing network functions. Local Area Network technology and protocols are discussed. Link, network, transport layer protocols, and security are introduced. TCP/IP networks are stressed. VoIP is used as an example throughout the course. Basic concepts of network performance evaluation are studied, both analytical and simulation techniques are considered.

Prerequisite(s): EECS 168 or 169 and EECS 461 or MATH 526.

EECS 565 - Introduction to Information and Computer Security

3 credit hours

An introduction to the fundamentals of cryptography and information and computer security. Introduces the basic concepts, theories, and protocols in computer security. Discusses how to apply such knowledge to analyze, design and manage secure systems in the real world. Topic covered: the basics of cryptography, software security, operating system security, database security, network security, privacy and anonymity, social engineering, digital forensics, etc.

Prerequisite(s): Corequisite: EECS 678 and Prerequisite: Upper-Level EECS Eligibility.

EECS 581 - Computer Science Design I

3 credit hours

The background and planning phase of a two-semester, team-oriented lecture/laboratory course involving the specification, design, implementation, and documentation of a significant software system. The course includes the consideration of project management, ethics, economics, and technical writing. Can be taken only during the senior year.

Prerequisite(s): Prerequisite: EECS 448. Co-Requsite: EECS 510 and EECS 560.

EECS 582 - Computer Science Design II

3 credit hours

The design and implementation phase of a two-semester, team-orientated lecture/laboratory course involving the specification, design, implementation, and documentation of a significant software system. The course includes the consideration of project management, ethics, economics, and technical writing. Can be taken only during the senior year.

Prerequisite(s): EECS 581

EECS 611 - Electromagnetic Compatibility

3 credit hours

A study of unwanted generation and reception of radio-frequency radiation from analog and digital electronic systems and how these emissions/receptions can be reduced. Topics covered include sources of radiation, grounding, shielding, crosstalk, electrostatic discharge, and practical design and layout schemes for reducing unwanted radiation and reception. Also covered are the major governmental electromagnetic compatibility (EMC) regulations and standards that apply to commercial electronic devices and system

Prerequisite(s): EECS 220 and EECS 312

EECS 622 - Microwave and Radio Transmission Systems

3 credit hours

Introduction to radio transmission systems. Topics include radio transmitter and receiver design, radiowave propagation phenomenology, antenna performance and basic design, and signal detection in the presence of noise. Students will design radio systems to meet specified performance measure.

Prerequisite(s): EECS 420 and EECS 461

EECS 628 - Fiber Optic Communication Systems

3 credit hours

Description and analysis of the key components in optical communications systems. Topics covered include quantum sources, propagation and dispersion characteristics of fiber, receiver characteristics, and system gain considerations.

Prerequisite(s): EECS 220 and PHSX 313 or equivalent and upper-level EECS eligibility

EECS 638 - Fundamentals of Expert Systems

3 credit hours

Basic information about expert systems: architecture of an expert system, building expert systems, uncertainty in expert systems, taxonomy of expert systems. Knowledge representation: first order logic, production systems, semantic nets, frames. Uncertainty in expert systems, one-valued approaches: probability theory, systems using Bayes' rule and systems using certainty theory; two-valued approaches: systems using Dempster-Shafer theory and system INFERNO; set-valued approaches: systems using fuzzy set theory and systems using rough set theory.

Prerequisite(s): EECS 560 or consent of instructor

EECS 639 - Introduction to Scientific Computing

3 credit hours

A basic introduction to scientific computing and numerical analysis. Topics include linear equation solving, least squares, nonlinear equation-solving, optimization, interpolation, numerical integration and differentiation, ordinary differential equations, and the fast Fourier transform (FFT). Vectorization, efficiency, reliability, and stability of numerical algorithms will be stressed. Applications of algorithms to real-world problems, such as image processing, medicine, electronic circuits, flight trajectories, and molecular modeling, will be emphasized. Students cannot receive credit for both EECS 639 and EECS/Math 781.

Prerequisite(s): MATH 127, MATH 290, EECS 168

EECS 644 - Introduction to Digital Signal Processing

3 credit hours

Discrete time signal and systems theory, sampling theorem, z-transforms, digital filter design, discrete Fourier transform, FFT, and hardware considerations.

Prerequisite(s): EECS 360

EECS 645 - Computer Architecture

3 credit hours

The structure and design of computing systems. Examination and analysis of computing systems. Examination and analysis of instruction set architectures, pipelined control and arithmetic units, vector processors, memory hierarchies, and performance evaluation.

Prerequisite(s): EECS 388

EECS 647 - Introduction to Database Systems

3 credit hours

Introduction to the concept of databases and their operations. Basic concepts, database architectures, storage structures and indexing, data structures: hierarchical, network, and relational database organizations. Emphasis on relational databases and retrieval languages SQL, QBE, and one based on relational algebra and relational calculus; brief description of predicate calculus. Theory of databases, normal forms, normalization, candidate keys, decomposition, functional dependencies, multi-valued dependencies. Introduction to the design of a simple database structure and a data retrieval language. Student cannot receive credit for both EECS 647 and EECS 746.

Prerequisite(s): EECS 448

EECS 649 - Introduction to Artificial Intelligence

3 credit hours

General concepts, search procedures, two-person games, predicate calculus and automated theorem proving, nonmonotonicic logic, probabilistic reasoning, rule based systems, semantic networks, frames, dynamic memory, planning, machine learning, natural language understanding, neural networks.

Prerequisite(s): EECS 368

EECS 660 - Fundamentals of Computer Algorithms

3 credit hours

Basic concepts and techniques in the design and analysis of computer algorithms. Models of computations. Simple lower bound theory and optimality of algorithms. Computationally hard problems and the theory of NP-Completeness. Introduction to parallel algorithms.

Prerequisite(s): EECS 560 and either EECS 461 or MATH 526

EECS 662 - Programming Languages

3 credit hours

Formal definition of programming languages, including specification of syntax and semantics. Simple statements including precedence, infix, prefix, and postfix notation. Global properties of algorithmic languages including scope of declaration, storage allocation, grouping of statements, binding time of constituents, subroutines, coroutines, and tasks. Run-time representation of program and data structures.

Prerequisite(s): EECS 368, EECS 388 and EECS 560

EECS 664 - Introduction to Digital Communication Systems

3 credit hours

An introduction to building digital communication systems in discrete time, including lectures and integrated laboratory exercises. Topics covered include signal spaces, baseband modulation, bandpass modulation, phase-locked loops, carrier phase recovery, symbol timing recovery, and basic performance analysis.

Prerequisite(s): EECS 360 and EECS 461

EECS 665 - Compiler Construction

4 credit hours

Compiler Construction (4). Compilation of simple expressions and statements. Organization of a compiler including symbol tables, lexical analysis, syntax analysis, intermediate and object code generation, error diagnostics, code optimization techniques and run-time structures in a block-structured language such as PASCAL or C. Programming assignments include using tools for lexer and parser generator, and intermediate, and object code generation techniques. Laboratory exercises will provide hands-on experience with the tools and concepts required for the programming assignments.

Prerequisite(s): EECS 368, EECS 448, EECS 510

EECS 670 - Introduction to Semiconductor Processing

3 credit hours

An overview of various processes to fabricate semiconductor devices and integrated circuits. Topics covered include crystal growth, oxidation, solid-state diffusion, ion implantation, photolithography, chemical vapor deposition, epitaxial growth, metalization, and plasma etching of thin films. (Same as C&PE 655)

Prerequisite(s): Senior standing in C&PE or EECS, or consent of instructor

EECS 672 - Introduction to Computer Graphics

3 credit hours

Foundations of 2D and 3D computer graphics. Structured graphics application programming. Basic 2D and 3D graphics algorithms (affine transformations, clipping, projections, visible line/surface determination, basic empirical lighting and shading models), overview of freeform curves and surfaces, and antialiasing.

Prerequisite(s): EECS 448

EECS 678 - Introduction to Operating Systems

4 credit hours

Introduction to Operating Systems (4). The objective of this course is to provide the students with the concepts necessary to enable them to: a) identify the abstract services common to all operating systems, b) define the basic system components that support the operating system’s machine independent abstractions on particular target architectures, c) consider how the design and implementation of different systems components interact and constrain one another, not merely how one or two important parts work in isolation, and d) understand the means by which fundamental problems in operating systems can be analyzed and addressed. Programming assignments address topics including process creation, inter-process communication, system call implementation, process scheduling and virtual memory. Laboratory exercises primarily focus on use of tools and concepts required for the programming assignments but include a small number of independent topics.

Prerequisite(s): EECS 388 and EECS 448

EECS 690 - Special Topics

1 - 3 credit hours

Arranged as needed to present appropriate material to groups of students. May be repeated for additional credit.

Prerequisite(s): Varies by topic, plus upper-level EECS eligibility and consent of instructor.

EECS 692 - Directed Reading

1 - 3 credit hours

Reading under the supervision of an instructor on a topic chosen by the student with the advice of the instructor. May be repeated for additional credit. Consent of the department required for enrollment.

Prerequisite(s): Upper-level EECS eligibility and consent of instructor.

EECS 700 - Special Topics

1-5 credit hours

Courses on special topics of current interest in electrical engineering, computer engineering, or computer science, given as the need arises. May be repeated for additional credit.

Prerequisite(s): Varies by topic.

EECS 711 - Security Management and Audit

3 credit hours

Administration and management of security of information systems and networks, intrusion detection systems, vulnerability analysis, anomaly detection, computer forensics, auditing and data management, risk management, contingency planning and incident handling, security planning, e-business and commerce security, privacy, traceability and cyber-evidence, human factors and usability issues, policy, legal issues in computer security.

Prerequisite(s): EECS 710

EECS 713 - High-Speed Digital Circuit Design

3 credit hours

Basic concepts and techniques in the design and analysis of high-frequency digital and analog circuits. Topics include: transmission lines, ground and power planes, layer stacking, substrate materials, terminations, vias, component issues, clock distribution, cross-talk, filtering and decoupling, shielding, signal launching.

Prerequisite(s): EECS 312 and senior or graduate standing. EECS 420 recommended.

EECS 718 - Graph Algorithms

3 credit hours

This course introduces students to computational graph theory and various graph algorithms and their complexities. Algorithms and applications covered will include those related to graph searching, connectivity and distance in graphs, graph isomorphism, spanning trees, shortest paths, matching, flows in network, independent and dominating sets, coloring and covering, and Traveling Salesman and Postman problems.

Prerequisite(s): EECS 560 or graduate standing with consent of instructor.

EECS 721 - Antennas

3 credit hours

Gain, Pattern, and Impedance concepts for antennas. Linear, loop, helical, and aperture antennas (arrays, reflectors, and lenses). Cylindrical and biconical antenna theory.

Prerequisite(s): EECS 360 AND EECS 420, or EECS 720.

EECS 723 - Microwave Engineering

3 credit hours

Survey of microwave systems, techniques, and hardware. Guided-wave theory, microwave network theory, active and passive microwave components.

Prerequisite(s): EECS 420

EECS 725 - Introduction to Radar Systems

3 credit hours

Basic radar principles and applications. Radar range equation. Pulsed and CW modes of operation for detection, ranging, and extracting Doppler information.

Prerequisite(s): EECS 360, EECS 420, and EECS 461. EECS 622 recommended

EECS 728 - Fiber-optic measurement and sensors

3 credit hours

The course will focus on fundamental theory and various methods and applications of fiber-optic measurements and sensors. Topics include: optical power and loss measurements, optical spectrum analysis, wavelength measurements, polarization measurements, dispersion measurements, PMD measurements, optical amplifier characterization, OTDR, optical components characterization and industrial applications of fiber-optic sensors.

Prerequisite(s): EECS 628 or equivalent.

EECS 730 - Introduction to Bioinformatics

3 credit hours

This course provides an introduction to bioinformatics. It covers computational tools and databases widely used in bioinformatics. The underlying algorithms of existing tools will be discussed. Topics include: molecular biology databases, sequence alignment, gene expression data analysis, protein structure and function, protein analysis, and proteomics.

Prerequisite(s): Data Structures class equivalent to EECS 560, and Introduction to Biology equivalent to BIOL 150, or consent of instructor.

EECS 731 - Introduction to Data Science

3 credit hours

This course covers topics in data collection, data transmission, and data analysis, in support of discoveries and innovations based on massive amounts of data. EECS 731 surveys current topics in data science. It provides a comprehensive review of theory, algorithms, and tools that are used in data science and prepares students to take in-depth following up courses in EECS. EECS 731 is a project-oriented course. It offers hands-on experience for students to integrate knowledge from a wide-range of topics in data science without dwelling on any particular subfield of data science.

Prerequisite(s): EECS 268 or experience with object oriented programming and large programs. MATH 290 or experience with linear algebra. EECS 461 or MATH 526 or experience with probability and statistics. Or consent from the instructor.

EECS 738 - Machine Learning

3 credit hours

“Machine learning is the study of computer algorithms that improve automatically through experience” (Tom Mitchell). This course introduces basic concepts and algorithms in machine learning. A variety of topics such as Bayesian decision theory, dimensionality reduction, clustering, neural networks, hidden Markov models, combining multiple learners, reinforcement learning, Bayesian learning etc. will be covered.

Prerequisite(s): Graduate standing in CS or CoE or consent of instructor.

EECS 739 - Parallel Scientific Computing

3 credit hours

This course is concerned with the application of parallel processing to real-world problems in engineering and the sciences. State-of-the-art serial and parallel numerical computing algorithms are studied along with contemporary applications. The course takes an algorithmic design, analysis, and implementation approach and covers an introduction to scientific and parallel computing, parallel computing platforms, design principles of parallel algorithms, analytical modeling of parallel algorithms, MPI programming, direct and iterative linear solvers, numerical PDEs and meshes, numerical optimization, GPU computing, and applications of parallel scientific computing.

Prerequisite(s): Math 122 or Math 126; Math 290; experience programming in C, C++, or Fortran; EECS 639 (or equivalent) Highly recommended: Math 127 or Math 223.

EECS 740 - Digital Image Processing

3 credit hours

This course gives a hands on introduction to the fundamentals of digital image processing. Topics include: image formation, image transforms, image enhancement, image restoration, image reconstruction, image compression, and image segmentation.

Prerequisite(s): EECS 672 or EECS 744

EECS 741 - Computer Vision

3 credit hours

This course gives a hands-on introduction to the fundamentals of computer vision. Topics include: image formation, edge detection, image segmentation, line-drawing interpretation, shape from shading, texture analysis, stereo imaging, motion analysis, shape representation, object recognition.

Prerequisite(s): EECS 672 or EECS 744

EECS 742 - Static Analysis

3 credit hours

This course presents an introduction to techniques for statically analyzing programs. Coverage includes theoretical analysis, definition and implementation of data flow analysis, control flow analysis, abstract interpretation, and type and effects systems. The course presents both the underlying definitions and pragmatic implementation of these systems.

Prerequisite(s): EECS 662 or EECS 665 or equivalent

EECS 743 - Advanced Computer Architecture

3 credit hours

This course will focus on the emerging technologies to build high-performance, low-power, and resilient microprocessors. Topics include multiprocessing, reliability-and-variability-aware computer architecture designs, energy-efficient computer systems, on-chip networks, 3D microprocessor designs, general-purpose computation on graphics processing units, and non-volatile computer memory. The course responds to VLSI technologies ability to provide increasing numbers of transistors and clock speeds to allow computer architects to build powerful microprocessors and computer systems and the challenges (e.g. resilience, energy-efficiency) that the growth in microprocessor performance is facing from the aggressive technology scaling.

Prerequisite(s): Prerequisite: EECS 643 or EECS 645, or equivalent. A good understanding of C/C++ and having basic Unix/Linux skills is required.

EECS 744 - Communications and Radar Digital Signal Processing

3 credit hours

The application of DSP techniques to specialized communications and radar signal processing subsystems. Topics include A-D converters, specialized digital filters, software receiver systems, adaptive subsystems and timing.

Prerequisite(s): Prerequisites: An undergraduate course in DSP such as EECS 644.

EECS 745 - Implementation of Networks

3 credit hours

Laboratory-focused implementation of networks. Topics include direct link networks (encoding, framing, error detection, reliable transmission, SONET, FDDI, network adapters, Ethernet, 802.11 wireless networks); packet and cell switching (ATM, switching hardware, bridges & extended LANs); internetworking (Internet concepts, IPv6, multicast, naming/DNS); end-to-end protocols (UDP, TCP, APIs and sockets, RPCs, performance); end-to-end data (presentation formatting, data compression, security); congestion control (queuing disciplines, TCP congestion control and congestion avoidance); high-speed networking (issues, services, experiences); voice over IP (peer-to-peer calling, call managers, call signaling, PBX and call attendant functionality).

Prerequisite(s): EECS 563 or EECS 780.

EECS 750 - Advanced Operating Systems

3 credit hours

This course will study advanced topics in operating systems for modern hardware platforms. The topics include: multicore CPU scheduling, cache and DRAM management, flash-based storage systems and I/O management, power/energy management, and cloud systems. It will discuss classical and recent papers in each of these topics. It will also study advanced resource management capabilities in recent Linux kernels. The course will consist of lectures, student presentations, and a term project.

Prerequisite(s): EECS 678 Introduction to Operating Systems.

EECS 753 - Embedded and Real Time Computer Systems

3 credit hours

This course will cover emerging and proposed techniques and issues in embedded and real time computer systems. Topics will include new paradigms, enabling technologies, and challenges resulting from emerging application domains

Prerequisite(s): EECS 645 and EECS 678

EECS 755 - Software Modeling and Analysis

3 credit hours

Modern techniques for modeling and analyzing software systems. Course coverage concentrates on pragmatic, formal modeling techniques that support predictive analysis. Topics include formal modeling, static analysis, and formal analysis using model checking and theorem proving systems.

Prerequisite(s): EECS 368 or equivalent.

EECS 759 - Estimation and Control of Unmanned Autonomous Systems

3 credit hours

An introduction to the modeling, estimation and control of unmanned autonomous systems. Topics include model identification, complementary filters, Kalman filters, attitude estimation, position estimation, attitude keeping controller, path planning, etc. The successful completion of this course will prepare students for advanced studies in robotics & controls. (Same as AE 759).

Prerequisite(s): MATH 627 or EECS 461 or equivalent, and AE 551 or EECS 444 or equivalent, or by consent of instructor.

EECS 762 - Programming Language Foundation I

3 credit hours

This course presents a basic introduction to the semantics of programming languages. The presentation begins with basic lambda calculus and mechanisms for evaluating lambda calculus terms. Types are introduced in the form of simply typed lambda calculus and techniques for type inference and defining type systems are presented. Finally, techniques for using lambda calculus to define, evaluate and type check common programming language constructs are presented.

Prerequisite(s): EECS 662 or equivalent.

EECS 764 - Analysis of Algorithms

3 credit hours

Models of computations and performance measures; asymptotic analysis of algorithms; basic design paradigms including divide-and-conquer, dynamic programming, backtracking, branch-and-bound, greedy method and heuristics; design and analysis of approximation algorithms; lower bound theory; polynomial transformation and the theory of NP-completeness; additional topics may be selected from arithmetic complexity, graph algorithms, string matching, and other combinatorial problems.

Prerequisite(s): EECS 660 or equivalent

EECS 765 - Introduction to Cryptography and Computer Security

3 credit hours

Comprehensive coverage to the fundamentals of cryptography and computer and communication security. This course serves as the first graduate level security course, which introduces the core concepts, theories, algorithms and protocols in computer and communication security, and also prepares students for advanced security courses. This course first covers the mathematical foundation of cryptography and its applications in computer security. The course also covers a wide range of topics: information and database security, software and computer systems security, network security, Internet and web security.

Prerequisite(s): EECS 678 and (EECS 780 or EECS 563), or the instructor's approval.

EECS 767 - Information Retrieval

3 credit hours

This class introduces algorithms and applications for retrieving information from large document repositories, including the Web. Topics span from classic information retrieval methods for text documents and databases, to recent developments in Web search, including: text algorithms, indexing, probabilistic modeling, performance evaluation, web structures, link analysis, multimedia information retrieval, social network analysis.

Prerequisite(s): EECS 647 or permission of instructor.

EECS 768 - Virtual Machines

3 credit hours

Understand the fundamental principles and advanced implementation aspects of key virtual machine concepts. Topics include principles of virtualization, binary translation, process and system level virtual machines, JIT compilation and optimizations in managed environments, garbage collection, virtual machine implementation issues, and virtual machine security. Includes in-depth coverage of the latest developments and research issues in the field of virtual machines.

Prerequisite(s): Prerequisites: EECS 665 and either EECS 643 or EECS 645 or consent of instructor.

EECS 769 - Information Theory

3 credit hours

Information theory is the science of operations on data such as compression, storage, and communication. It is one of the few scientific fields fortunate enough to have an identifiable beginning - Claude Shannon's 1948 paper. The main topics of mutual information, entropy, and relative entropy are essential for students, researchers, and practitioners in such diverse fields as communications, data compression, statistical signal processing, neuroscience, and machine learning. The topics covered in this course include mathematical definitions and properties of information, mutual information, source coding theorem, lossless compression of data, optimal lossless coding, noisy communication channels, channel coding theorem, the source channel separation theorem, multiple access channels, broadcast channels, Gaussian noise, time-varying channels, and network information theory.

Prerequisite(s): EECS 461 or an equivalent undergraduate probability course

EECS 773 - Advanced Graphics

3 credit hours

Advanced topics in graphics and graphics systems. Topics at the state of the art typically selected from: photorealistic rendering; physically-based lighting models; ray tracing; radiosity; physically-based modeling and rendering; animation; general texture mapping techniques; point-based graphics; collaborative techniques; and others

Prerequisite(s): EECS 672 or permission of instructor.

EECS 774 - Geometric Modeling

3 credit hours

Introduction to the representation, manipulation, and analysis of geometric models of objects. Implicit and parametric representations of curves and surfaces, with an emphasis on parametric freeform curves and surfaces such as Bezier and Nonuniform Rational B-Splines (NURBS). Curve and surface design and rendering techniques. Introduction to solid modeling: representations and basic algorithms. Projects in C/C++ using OpenGL.

Prerequisite(s): EECS 672 or permission of instructor.

EECS 775 - Visualization

3 credit hours

Data representations, algorithms, and rendering techniques typically used in Visualization applications. The emphasis is on Scientific Visualization and generally includes topics such as contouring and volumetric rendering for scalar fields, glyph and stream (integral methods) for vector fields, and time animations. Multidimensional, multivariate (MDMV) visualization techniques; scattered data interpolation; perceptual issues

Prerequisite(s): General knowledge of 3D graphics programming or permission of instructor.

EECS 776 - Functional Programming and Domain Specific Languages

3 credit hours

An introduction to functional programming. Topics include learning how to program in Haskell; IO and purity in software engineering; functional data structures and algorithms; monads and applicative functors; parsing combinators; Domain Specific Languages (DSLs) and DSL construction; advanced type systems; making assurance arguments; testing and debugging.

Prerequisite(s): Prerequisites: EECS 368 or equivalent or consent of instructor.

EECS 780 - Communication Networks

3 credit hours

Comprehensive in-depth coverage to communication networks with emphasis on the Internet and the PSTN (wired and wireless, and IoT – Internet of Things). Extensive coverage of protocols and algorithms will be presented at all levels, including: social networking, overlay networks, client/server and peer-to-peer applications; session control; transport protocols, the end-to-end arguments and end-to-end congestion control; network architecture, forwarding, routing, signaling, addressing, and traffic management, programmable and software-defined networks (SDN); quality of service, queueing and multimedia applications; LAN architecture, link protocols, access networks and MAC algorithms; physical media characteristics and coding; network security and information assurance; network management.

Prerequisite(s): EECS 563 or equivalent or permission of instructor.

EECS 781 - Numerical Analysis I

3 credit hours

Finite and divided differences. Interpolation, numerical differentiation, and integration. Gaussian quadrature. Numerical integration of ordinary differential equations. Curve fitting. (Same as MATH 781).

Prerequisite(s): MATH 320 and knowledge of a programming language

EECS 782 - Numerical Analysis II

3 credit hours

Direct and interactive methods for solving systems of linear equations. Numerical solution of partial differential equations.Numerical determination of eigenvectors and eigenvalues. Solution of nonlinear equations. (Same as MATH 782).

Prerequisite(s): EECS 781

EECS 784 - Science of Communication Networks

3 credit hours

Comprehensive introduction to the fundamental science that is the basis for the architecture, design, engineering, and analysis of computer networks. Topics covered will include foundations on: Structure of networks: graph theory, complex systems analysis, centrality, spectral analysis, network flows, and network topology; Identification of network entities: naming, addressing, indirection, translation, and location; Operation of protocols and information transfer: automata, control theory, Petri nets, layering and cross-layering, protocol data units; Policy and tussle: game theory, decision theory; Resilience: dependability (reliability, availability, and maintainability), performability, fault tolerance, and survivability. Open-source tools will be used for network modelling and analysis.

Prerequisite(s): EECS upper-level eligibility, graduate standing, or permission of the instructor.

EECS 786 - Digital VLSI (Very-Large-Scale Integration)

3 credit hours

This course covers the basic concepts of Integrated Circuit (IC) design, various methods of designing VLSI circuits, and techniques to analyze and optimize performance metrics, such as: speed, area, power and signal integrity. Clocking, interconnect and scaling issues of IC will also be discussed. The topic will cover device, interconnect and circuit level implementation issues of both logic and memory circuits. It will also briefly introduce the high performance issues, fabrication technologies and system level implementation approaches of IC to establish bridges to the advanced courses.

Prerequisite(s): Prerequisite: EECS 312

EECS 788 - Analog Integrated Circuit Design

3 credit hours

This course covers the analysis and design of analog and mixed signal integrated circuits, with an emphasis on design principles for realizing state-of-the-art analog circuits. Modern circuit design is a "mixed signal" endeavor thanks to the availability of sophisticated process technologies that allow bipolar and CMOS (Complementary Metal Oxide Semiconductor), power and signal, passive and active components on the same die. It is then up to the circuit designer's creativity and inclination to assemble these components into the analog and/or logic building blocks. The course will provide the critical concepts by giving physical and intuitive explanations in addition to the quantitative analysis of important analog building block circuits. First-order hand calculations and extensive computer simulations are utilized for performance evaluation and circuit design.

Prerequisite(s): Prerequisite: EECS 412

EECS 800 - Special Topics

1-5 credit hours

Advanced courses on special topics of current interest in electrical engineering, computer engineering, or computer science, given as the need arises. May be repeated for additional credit.

Prerequisite(s): Variable

EECS 801 - Directed Graduate Readings

1-3 credit hours

Graduate level directed readings on a topic in electrical engineering, computer engineering, or computer science, mutually agreed-on by the student, the instructor and the graduate committee. May be repeated for credit on another topic for a total of 3 credit hours. Consent of instructor and graduate committee approval.

Prerequisite(s): Consent of instructor and graduate committee approval.

EECS 802 - EECS Colloquium and Seminar on Professional Issues

1.0 credit hours

A colloquium/seminar series in which presentation are provided on a broad variety of scholarly and professional topics. Topics related to the issues of responsible scholarship in the fields of computing and electrical engineering will be discussed. Student are also required to attend a series of colloquia and submit written reports. Course will be graded Satisfactory/Fail and is required for all EECS graduate students.

Prerequisite(s): Graduate standing in the EECS Department.

EECS 812 - Software Requirements Engineering

3 credit hours

Objectives, processes, and activities of requirements engineering and requirements management; characteristics of good requirements; types of requirements; managing changing requirements; languages, notations and methodologies; formal and semi-formal methods of presenting and validating the requirements; requirements standards; tracability issues.

Prerequisite(s): EECS 810

EECS 820 - Advanced Electromagnetics

3 credit hours

A theorem-based approach to solving Maxwell's equations for modeling electromagnetic problems encountered in microwave systems, antennas, scattering. Topics include waves, source modeling, Schelkunoff equivalence principle, scattered field formulations, electromagnetic induction, reciprocity principles, Babinet's principle, and construction of solutions in various coordinate systems.

Prerequisite(s): EECS 420.

EECS 823 - Microwave Remote Sensing

3 credit hours

Description and analysis of basic microwave remote sensing systems including radars and radiometers as well as the scattering and emission properties of natural targets. Topics covered include plane wave propagation, antennas, radiometers, atmospheric effects, radars, calibrated systems, and remote sensing applications.

Prerequisite(s): EECS 420 and EECS 622

EECS 828 - Advanced Fiber-Optic Communications

3 credit hours

An advanced course in fiber-optic communications. The course will focus on various important aspects and applications of modern fiber-optic communications, ranging from photonic devices to systems and networks. Topics include: advanced semiconductor laser devices, external optical modulators, optical amplifiers, optical fiber nonlinearities and their impact in WDM and TDM optical systems, polarization effect in fiber-optic systems, optical receivers and high-speed optical system performance evaluation, optical soliton systems, lightwave analog video transmission, SONET & ATM optical networking and advanced multi-access lightwave networks.

Prerequisite(s): EECS 628 or equivalent

EECS 830 - Advanced Artificial Intelligence

3 credit hours

A detailed examination of computer programs and techniques that manifest intelligent behavior, with examples drawn from current literature. The nature of intelligence and intelligent behavior. Development of, improvement to, extension of, and generalization from artificially intelligent systems, such as theorem-provers, pattern recognizers, language analyzers, problem-solvers, question answerers, decision-makers, planners, and learners.

Prerequisite(s): Graduate standing in the EECS department or Cognitive Science or permission of the instructor.

EECS 831 - Introduction to Systems Biology

3 credit hours

This course provides an introduction to systems biology. It covers computational analysis of biological systems with a focus on computational tools and databases. Topics include: basic cell biology, cancer gene annotation, micro RNA identification, Single Nucleotide Polymorphism (SNP) analysis, genetic marker identification, protein-DNA interaction, computational Neurology, vaccine design, cancer drug development, and computational developmental biology.

Prerequisite(s): Prerequisite: Introduction to Bioinformatics equivalent to EECS 730, or consent of instructor. LEC

EECS 837 - Data Mining

3 credit hours

Extracting data from data bases to data warehouses. Preprocessing of data: handling incomplete, uncertain and vague data sets. Discretization methods. Methodology of learning from examples: rules of generalization and control strategies. Typical learning systems: ID3, AQ, C4.5 and LERS. Validation of knowledge. Visualization of knowledge bases. Data mining under uncertainty, using approaches based on probability theory, fuzzy set theory and rough set theory.

Prerequisite(s): Graduate standing in CS or CoE or consent of instructor.

EECS 838 - Applications of Machine Learning in Bioinformatics

3 credit hours

This course is introduction to the application of machine learning methods in bioinformatics. Major subjects include: biological sequence analysis, microarray interpretation, protein interaction analysis, and biological network analysis. Common biological and biomedical data types and related databases will also be introduced. Students will be asked to present some selected research papers.

Prerequisite(s): EECS 730 and EECS 738

EECS 839 - Mining Special Data

3 credit hours

Problems associated with mining incomplete and numerical data. The MLEM2 algorithm for rule induction directly from incomplete and numerical data. Association analysis and the Apriori algorithm. KNN and other statistical methods. Mining financial data sets. Problems associated with imbalanced data sets and temporal data. Mining medical and biological data sets. Induction of rule generations. Validation of data mining: sensitivity, specificity, and ROC analysis.

Prerequisite(s): Graduate standing in CS or CoE or consent of instructor

EECS 843 - Programming Language Foundation II

3 credit hours

This course presents advanced topics in programming language semantics. Fixed point types are presented followed by classes of polymorphism and their semantics. System F and type variables are presented along with universal and existential types. The lambda cube is introduced along with advanced forms of polymorphism. Several interpreters are developed implementing various type systems and associated type inference algorithms.

Prerequisite(s): EECS 762

EECS 844 - Adaptive Signal Processing

3 credit hours

This course presents the theory and application of adaptive signal processing. Topics include adaptive filtering, mathematics for advanced signal processing, cost function modeling and optimization, signal processing algorithms for optimum filtering, array processing, linear prediction, interference cancellation, power spectrum estimation, steepest descent, and iterative algorithms.

Prerequisite(s): Prerequisite: Background in fundamental signal processing (such as EECS 644) Co-requisite: EECS 861

EECS 861 - Random Signals and Noise

3 credit hours

Fundamental concepts in random variables , random process models, power spectral density. Application of random process models in the analysis and design of signal processing systems, communication systems and networks. Emphasis on signal detection, estimation, and analysis of queues. This course is a prerequisite for most of the graduate level courses in radar signal processing, communication systems and networks.

Prerequisite(s): An undergraduate course in probability and statistics, and signal processing.

EECS 862 - Principles of Digital Communication Systems

3 credit hours

A study of communication systems using noisy channels. Principal topics are: information and channel capacity, baseband data transmission, digital carrier modulation, error control coding, and digital transmission of analog signals. The course includes a laboratory/computer aided design component integrated into the study of digital communication systems.

Prerequisite(s): EECS 562. Corequiesite: EECS 861.

EECS 863 - Network Analysis, Simulation, and Measurements

3 credit hours

Prediction of communication network performance using analysis, simulation, and measurement. Topics include: an introduction to queueing theory, application of theory to prediction of communication network and protocol performance, and analysis of scheduling mechanisms. Modeling communication networks using analytic and simulation approaches, model verification and validation through analysis and measurement, and deriving statistically significant results. Analysis, simulation, and measurement tools will be discussed.

Prerequisite(s): EECS 461 or Math 526, and EECS 563 or EECS 780

EECS 865 - Wireless Communication Systems

3 credit hours

Mobile radio channels, models for multipath fading channels ( Rayleigh and Rician), communication techniques for multipath fading channels, OFDM and spread spectrum systems, diversity combining and RAKE receivers, cellular concepts (frequency reuse, and interference), multiple access techniques (FDMA, CDMA, and TDMA), examples of cellular radio and wireless LAN standards and systems (GSM, 3GPP, IEEE 801.11)

Prerequisite(s): EECS 861 and EECS 862

EECS 866 - Network Security

3 credit hours

This course provides in-depth coverage on the concepts, principles, and mechanisms in network security and secure distributed systems. The topics that will be covered include: network security primitives, risks and vulnerabilities, authentication, key management, network attacks and defense, secure communication protocols, intrusion detection, exploit defenses, traffic monitoring and analysis, and privacy mechanisms.

Prerequisite(s): EECS 765 and (EECS 780 or EECS 563), or the instructor's approval.

EECS 868 - Mathematical Optimization with Applications

3 credit hours

A mathematical study of the minimization of functions. The course provides an introduction to the mathematical theory, implementation, and application of a variety of optimization techniques, with an emphasis on real-world applications. Optimization problem formulation. Unconstrained and constrained minimization, including conditions for optimality. Specific techniques for solving linear and nonlinear programming problems. Convergence of algorithms.

Prerequisite(s): Math 590 or EECS 639, or the consent of the instructor.

EECS 869 - Error Control Coding

3 credit hours

A study of communication channels and the coding problem. An introduction to finite fields and linear block codes such as cyclic, Hamming, Golay, BCH, and Reed-Solomon. Convolutional codes and the Viberbi algorithm are also covered. Other topics include trellis coded modulation, iterative (turbo) codes, LDPC codes.

Prerequisite(s): EECS 562 or equivalent.

EECS 881 - High-Performance Networking

3 credit hours

Comprehensive coverage of the discipline of high-bandwidth low-latency networks and communication, including high bandwidth-×-delay products, with an emphasis on principles, architecture, protocols, and system design. Topics include high-performance network architecture, control, and signaling; high-speed wired, optical, and wireless links; fast packet, IP, and optical switching; IP lookup, classification, and scheduling; network processors, end system design and protocol optimization, network interfaces; storage networks; data-center networks, end-to-end protocols, mechanisms, and optimizations; high-bandwidth low-latency applications and cloud computing. Principles will be illustrated with many leading-edge and emerging protocols and architectures.

Prerequisite(s): Either EECS 563, EECS 780, or permission of the instructor.

EECS 882 - Mobile Wireless Networking

3 credit hours

Comprehensive coverage of the disciplines of mobile and wireless networking, with and emphasis on architecture and protocols. Topics include cellular telephony, MAC algorithms, wireless PANs, LANs, MANs, and WANs; wireless and mobile Internet; mobile ad hoc networking; mobility management, sensor networks; satellite networks; and ubiquitous computing.

Prerequisite(s): Either EECS 563, EECS 780 or permission of the instructor.

EECS 888 - Internet Routing Architectures

3 credit hours

A detailed study of routing in IP networks. Topics include evolution of the Internet architecture, IP services and network characteristics, an overview of routing protocols, the details of common interior routing protocols and interdomain routing protocols, and the relationship between routing protocols and implementation of policy. Issues will be illustrated through laboratories based on common routing platforms.

Prerequisite(s): EECS 745

EECS 891 - Graduate Problems

1-5 credit hours

Directed studies of advanced phases of electrical engineering, computer engineering, computer science or information technology not covered in regular graduate courses, including advanced laboratory work, special research, or library reading.

Prerequisite(s): Prerequisite: Consent of instructor.

EECS 899 - Master’s Thesis

1-6 credit hours

EECS 900 - Seminar

0.5-3 credit hours

Group discussions of selected topics and reports on the progress of original investigations

Prerequisite(s): Consent of Instructor

EECS 940 - Theoretic Foundation of Data Science

3 credit hours

A review of statistical and mathematical principles that are utilized in data mining and machine learning research. Covered topics include asymptotic analysis of parameter estimation, sufficient statistics, model selection, information geometry, function approximation and Hilbert spaces.

Prerequisite(s): Prerequisite: EECS 738, EECS 837, EECS 844 or equivalent.

EECS 965 - Detection and Estimation Theory

3 credit hours

Detection of signals in the presence of noise and estimation of signal parameters. Narrowband signals, multiple observations, signal detectability, and sequential detection. Theoretical structure and performance of the receiver.

Prerequisite(s): EECS 861

EECS 983 - Resilient and Survivable Networking

3 credit hours

Graduate research seminar that provides an overview of the emerging field of survivable, disruption-tolerant, and challenged networks. These networks aim to remain operational and provide an acceptable level of service in the face of a number of challenges including: natural faults of network components; failures due to misconfiguration or operational errors; attacks against the network hardware, software, or protocol infrastructure; large-scale natural disasters; unpredictably long delay paths either due to length (e.g. satellite and interplanetary) or as a result of episodic connectivity; weak and episodic connectivity and asymmetry of wireless channels; high-mobility of nodes and subnetworks; unusual traffic load (e.g. flash crowds). Multi-level solutions that span all protocol layers, planes, and parts of the network will be systemically and systematically covered. In addition to lectures, students read and present summaries of research papers, and execute a project.

Prerequisite(s): EECS 780; previous experience in simulation desirable.

EECS 998 - Post-Master’s Research

1-6 credit hours

EECS 999 - Doctoral Dissertation

1-12 credit hours