All schools & programs >

School of Engineering

Visit their website » Print...

Principal Course Distribution Requirement

Principal courses offer introductions to the breadth of disciplines in the College. They acquaint students with the subject matter in an area, with the types of questions that are asked about that subject matter, with the knowledge that has been developed and is now basic to the area, and with the methods and standards by which claims to truth are judged.

Students must complete courses in topical groups in three major divisions (humanities, natural sciences and mathematics, and social sciences). For the B.A., three courses are required from each division, with no more than one course from any topical group. The B.G.S. requires two courses from each division, with no more than one from any topical group. To fulfill the requirement, a course must be designated as a principal course according to the codes listed below.

These are the major divisions, their topical subgroups, and the codes that identify them:

Humanities

  • HT: Historical studies
  • HL: Literature and the arts
  • HR: Philosophy and religion

Natural Sciences and Mathematics

  • NB: Biological sciences
  • NE: Earth sciences
  • NM: Mathematical sciences
  • NP: Physical science

Social Sciences

  • SC: Culture and society
  • SI: Individual behavior
  • SF: Public affairs

No course may fulfill both a principal course distribution requirement and a non-Western culture or second-level mathematics course requirement. Laboratory science courses designated as principal courses may fulfill both the laboratory science requirement and one of the distribution requirements. No free-standing laboratory course may by itself fulfill either the laboratory science requirement or a principal course requirement. Students should begin taking principal courses early in their academic careers. An honors equivalent of a principal course may fulfill a principal course requirement.

View all approved principal course distribution courses »

Non-Western Culture Requirement

A non-Western culture course acquaints students with the culture, society, and values of a non-Western people, for example, from Asia, the Pacific Islands, the Middle East, or Africa. Students must complete one approved non-Western culture course.

One approved non-Western culture course is required. Occasionally courses with varying topics fulfill the non-Western culture course requirement. See the Schedule of Classes for details. These courses are coded NW.

View all approved non-Western culture courses »

Transfer and Earned Credit Course Codes

These codes are used to evaluate transfer credit and to determine which academic requirements a course meets.

  • H: Humanities
  • N: Natural Sciences and Mathematics
  • S: Social Sciences
  • W: World Civilization and Culture
  • U: Undesignated Elective Credit (course does not satisfy distribution requirement)

All Engineering courses

Show courses in ENGR with a course number to
worth in .

There are 632 results.

Identifying critical information assets; information security, integrity, and availability; security risks and risk avoidance; security models; access control mechanisms; computer viruses, worms, Trojan horses and other malicious login; encryption, cryptography, and key management technologies; operating systems security; database security; network security; e-commerce security; security policies; management and auditing. Prerequisite: Graduate standing in EECS. LEC
View current sections...
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, legal issues in computer security. Prerequisite: EECS 710. LEC
View current sections...
Introduction to the basic concepts, components, protocols, and software tools to achieve secure communication in a public network. The concept of encryption, integrity, authentication, security models, and the robustness analysis. Emphasis on the application level protocols and vulnerabilities: firewalls, viruses, worm attack, Trojan horses, password security, secure multicast, biometrics, VPNs, internet protocols such as SSL, IPSec, PGP, and SNMP. The policies for access control, user privacy, and trust establishment and abuse in open environments such as eBay. Prerequisite: EECS 563 or EECS 780. LEC
View current sections...
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: EECS 312 and senior or graduate standing. EECS 420 recommended. LEC
View current sections...
Formal language generation by grammars, recognition by automata (finite and pushdown automata, Turing machines), and equivalence of these formulations; elementary containment and closure properties. Emphasis on context-free, deterministic context-free and regular languages. Prerequisite: EECS 510 or equivalent. LEC
View current sections...
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: EECS 560 or graduate standing with consent of instructor. LEC
View current sections...
Topics in electromagnetics relevant to wireless communications, otpics and fiberoptics, radar, and remote sensing. Subjects covered include space waves, guided waves, radiation and antennas, scattering, electromagnetic properties of materials, and optics. Prerequisite: EECS 420 or equivalent. LEC
View current sections...
Gain, Pattern, and Impedance concepts for antennas. Linear, loop, helical, and aperture antennas (arrays, reflectors, and lenses). Cylindrical and biconical antenna theory. Prerequisite: EECS 360, EECS 420, or EECS 720. Infrequently offered. LEC
View current sections...
Propositional calculus. First order theories and model theory. Elementary arithmetic and Godel's incompleteness theorems. (Same as MATH 722.) Prerequisite: MATH 765 or MATH 791, or equivalent evidence of mathematical maturity. LEC
View current sections...
Survey of microwave systems, techniques, and hardware. Guided-wave theory, microwave network theory, active and passive microwave components. The four-hour version of the course includes a laboratory. Prerequisite: EECS 420. LEC
View current sections...
Basic radar principles and applications. Radar range equation. Pulsed and CW modes of operation for detection, ranging, and extracting Doppler information. Prerequisite: EECS 360, EECS 420, EECS 461. EECS 622 recommended. LEC
View current sections...
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: EECS 628 or equivalent. LEC
View current sections...
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: Data Structures class equivalent to EECS 560, and Introduction to Biology equivalent to BIOL 150, or consent of instructor. LEC
View current sections...
Computer-based theorem-proving methods for selected domains such as plane geometry, symbolic integral calculus, and propositional calculus are reviewed. Mechanical theorem-proving procedures for the first-order predicate calculus are studied in depth. Includes resolution, semantic resolution, hyper-resolution, linear resolution, and paramodulation. Applications of these procedures to areas such as proofs of program correctness, deductive question answering, problem solving, and program synthesis. Prerequisite: EECS 730 and a knowledge of mathematical logic equivalent to that supplied by EECS 210. Infrequently offered. LEC
View current sections...
"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: Graduate standing in CS or CoE or consent of instructor. LEC
View current sections...
This course is concerned with the application of parallel processing to problems in the natural sciences and engineering. State-of-the-art computing methodologies are studied along with contemporary applications. The course takes a performance-oriented applied approach, with attention to parallel algorithms, parallel architecture, compilation issues, and system evaluation. Prerequisite: Graduate standing or consent of instructor and experience with C, C++, or FORTRAN. LEC
View current sections...
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: EECS 672 or EECS 744. LEC
View current sections...
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: EECS 672 or EECS 744. LEC
View current sections...
This course presents an introduction to techniques for statically analyzing programs. Coverage includes theoretical analysis, definition and implementation of data flow analysis, abstract interpretation, and type and effects systems. The course presents both the underlying definitions and pragmatic implementation of these systems. Prerequisite: EECS 665 or EECS 662 or equivalent. LEC
View current sections...
EECS 745 is a laboratory-focused implementation of networks. Topics include direct link networks (encoding, framing, error detection, reliable transmission, SONET, FDDL, network adapters, Ethernet, 802.11 wireless networks); packet and cell switching (ATM, switching hardware, bridges and 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 signalling, PBX and call attendant functionality). Prerequisite: EECS 563 or EECS 780. LEC
View current sections...
Introduction to the concept of databases and their operations. Basic database concepts, architectures, and data storage structures and indexing. Though other architectures are discussed, focus is on relational databases and the SQL retrieval language. Normalization, functional dependencies, and multivalued dependencies also covered. Culminates in the design and implementation of a simple database with a web interface. Prerequisite: EECS 448 or consent of instructor. Students cannot receive credit for both EECS 647 and EECS 746. LEC
View current sections...
Design, construction, and programming of mobile robots. Topics include computational hardware, designing and prototyping, sensors, mechanics, motors, power, robot programming, robot design principles, and current research in mobile robotics. Prerequisite: Knowledge of at least one modern programming language. LEC
View current sections...
General concepts of intelligent problem solving, rule-based systems, distributed AI, reasoning under uncertainty, case-based reasoning, subsymbolic techniques. Prerequisite: At least one class in Artificial Intelligence. LEC
View current sections...
This course builds on the foundation established by an introductory course in operating systems concepts (e.g. EECS 678). Some previously covered topics are revisited in far greater detail, including code review of relevant portions of the Linux kernel source code. Examples include: computation representation by processes, system calls, interrupt processing and interrupt concurrency, process execution scheduling, and concurrency control methods. Advanced topics, such as system performance analysis, time keeping, clock synchronization, virtualization, real-time implications for system design and scheduling, and device driver implementation are introduced for the first time. Approximately one-quarter to one-third of the class is devoted to reading, presenting and discussion conference and journal papers either illustrating classic breakthroughs in system architectures and methods or current research issues. Selection of the specific papers is done each semester, and students in the class are encouraged to suggest candidate topics and/or papers for consideration. Prerequisite: An undergraduate course in operating systems fundamentals. For example, EECS 678 or equivalent. LEC
View current sections...
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: EECS 645 and EECS 678. LEC
View current sections...
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: EECS 368 or equivalent. LEC
View current sections...
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: EECS 360, or an equivalent undergraduate course in signals and systems; EECS 461, or an equivalent undergraduate course in probability. LEC
View current sections...
An investigation of alternative programming paradigms and their representative effect on programming expressiveness and style. Emphasis is on a comparative understanding of a spectrum of programming paradigms, with some facility in the use of at least one typical language representative of each paradigm studied. The course will review and investigate as appropriate imperative, functional, object-oriented, parallel, and logical programming paradigms, plus additional paradigms as relevant. Prerequisite: EECS 662 or EECS 807 or equivalent. LEC
View current sections...
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: EECS 662 or equivalent. LEC
View current sections...
This course covers the latest trends in advanced computer architecture for multiprocessor systems on chip for embedded and real time systems (MPSoC). Topics covered include multicore architectures, modeling abstractions, run time systems, and Hw/Sw co-design techniques. Prerequisite: EECS 678 and EECS 645 or equivalents. LEC
View current sections...
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: EECS 660 or EECS 805 or equivalent. LEC
View current sections...
Connections between network customers and the network come in many forms, wireless data systems, e.g., IEEE 802.16, wireless cellular systems, e.g. 3G, coax cable networks, e.g., DOSCIS, fiber optic communications systems, e.g., EPON, copper twisted pair, e.g., DSL, and powerline communications systems. All of these systems use various resource sharing strategies. The resource sharing strategy is matched to the necessities of specific systems as well as their operating environments. There are commonalities between these strategies as well as differences. This course will look at resource sharing from a general perspective and then examine specific systems to underscore their commonalities and differences. Systems to be studied in detail include, DOSCIS, IEEE 802.16/Wi-Max, WCDMA, HSDPA/HSUPA, EV-DO, EPON, ZigBee/IEEE 802.15.4, powerline networks. The use of cognitive radio communications technologies in future access networks will be introduced. Prerequisite: EECS 461 and EECS 563 or EECS 780. LEC
View current sections...
The objective of this course is to give students a hands on introduction to information retrieval systems. Classic textual information retrieval systems are studied, followed by presentation of current research in the area. Topics include: file structures, term-weighting schemes, text preprocessing, World Wide Web search engines, multimedia retrieval systems, artificial intelligence applications. Prerequisite: EECS 647 or permission of instructor. LEC
View current sections...
Advanced topics in graphics and graphics systems. Topics at the state of the art are 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: EECS 672 or permission of instructor. LEC
View current sections...
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 base algorithms. Projects in C/C++ using OpenGL. Prerequisite: EECS 672 or permission of instructor. LEC
View current sections...
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: General knowledge of 3D graphics programming or instructor's permission. LEC
View current sections...
Comprehensive in-depth coverage to communication networks with emphasis on the Internet and the PSTN (wired and wireless). Extensive examples of protocols and algorithms will be presented at all levels, including: 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, signalling, addressing, and traffic management; quality of service, basic queuing (basic M/M/1 and Little's law) and multimedia applications; LAN architecture, link protocols, access networks and MAC algorithms; physical media characteristics and coding; network security and information assurance; network management. Students cannot receive credit for both EECS 563 and EECS 780. Prerequisite: EECS 168 and EECS 461. LEC
View current sections...
Finite and divided differences. Interpolation, numerical differentiation, and integration. Gaussian quadrature. Numerical integration of ordinary differential equations. Curve fitting. (Same as MATH 781.) Prerequisite: MATH 320 and knowledge of a programming language. LEC
View current sections...
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: EECS 781. LEC
View current sections...
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: Variable. LEC
View current sections...
Graduate level directed readings on a topic in electrical engineering, computer engineering, or computer science, mutually agreed-on by the student and instructor. May be repeated for credit on another topic. Prerequisite: Consent of instructor. RSH
View current sections...
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: Graduate standing in the EECS Department. LEC
View current sections...
Practical concepts of software engineering with a focus on management issues as well as formalism; modern software development process models; project management, requirements analysis, specification, design, implementation, testing, maintenance; metrics and planning. The course is intended for EECS graduate students (focusing in software engineering or computer science) as well as others with a strong interest in software engineering methodologies. The course will be project-intensive and will serve as a preparation for other graduate software engineering courses. Prerequisite: EECS 448 and EECS 560 or equivalent. Not open to students who have taken EECS 848. LEC
View current sections...
Process management in the context of software development; building productive teams; measuring performance; management issues in the creation, development, and maintenance of software. Various estimate techniques, planning, risk analysis, project administration, and configuration management; fundamentals of software process modeling and definition; process improvement, frameworks for quality software, process properties and measurements, capability maturity evaluation, validation and verification, applications of TQM and SQA to software process improvement. Prerequisite: EECS 810. LEC
View current sections...
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; traceability issues. Prerequisite: EECS 810. LEC
View current sections...
Software quality engineering as an integral facet of development, from requirements through deliver, maintenance, and process improvement; how to carry out inspections, manual and automated static analysis techniques, fundamental concepts in software testing, verification, validation, test case selection, testing strategies such as black-box testing, white-box testing, integration testing, regression testing, systems testing, acceptance testing, design for testability, fundamental concepts in software integration, configuration management, models for quality assurance; documentation, industry, and government standards for quality. Prerequisite: EECS 810. LEC
View current sections...
Abstract data types, objects and classes, class associations, modeling with objects, domain modeling, use case modeling, interactive and incremental development, object-oriented analysis and design, components, frameworks, UML and Unified Process, reusability, design patterns, object management, and CORBA. Prerequisite: EECS 810. LEC
View current sections...
Design methodologies, software architectural qualities; architectural styles; architecture and design; common architectural patterns and reuse; domain specific architectures; tradeoff analysis, software architecture case studies, architectural styles; the analysis of an architecture. Prerequisite: EECS 810 and EECS 816. LEC
View current sections...
Introduction to the mathematical background, basic concepts, components, and protocols to enforce secrecy, integrity, and privacy through cryptographic mechanisms. The concept of symmetric and asymmetric encryption, integrity verification, authentication, key establishment and update, and authorization. Emphasis on the design of protocols that apply and integrate various modules to achieve safety objectives: time-stamping, digital signature, bit commitment, fair coin-flip, zero knowledge proof, oblivious transfer, and digital cash. The policies for key generation and management, information storage and access control, legal issues, and design of protocols for real applications. Prerequisite: EECS 268, EECS 563 or EECS 780 and Linear Algebra. LEC
View current sections...
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: EECS 420 and EECS 622. LEC
View current sections...
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 measurement and discrimination, real-aperture side-looking airborne radars, synthetic-aperture side-looking airborne radar systems, scattering measurements, physical mechanisms and empirical models for scattering and emission. Prerequisite: EECS 823. LEC
View current sections...
Description and analysis of radars of various types. Resolution in angle, range, and speed. Ambiguities. Return from point and area targets. Detection in the presence of noise and fading. Tracking and MTI. Amplitude measurement. Imaging radars. Prerequisite: EECS 360, EECS 420, and EECS 461. LEC
View current sections...
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 solution systems, lightwave analog video transmission, SONET & ATM optical networking, and advanced multi-access lightwave networks. Prerequisite: EECS 628 or equivalent. LEC
View current sections...
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: Graduate standing in the EECS department or Cognitive Science or permission of the instructor. LEC
View current sections...
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 development biology. Prerequisite: Introduction to Bioinformatics equivalent to EECS 730, or consent of instructor. LEC
View current sections...
Fundamental theory of adaptive systems. Evolution of artificial neural networks and training algorithms. Pattern classification, function approximation, and system optimization. Introduction to fuzzy set theory and neuro-fuzzy models for pattern classification. Application of neural networks in signal and image processing problems. Pattern classification for biological systems. Prerequisite: Graduate standing in the EECS department or permission of instructor. LEC
View current sections...
This course emphasizes the applications of computational algorithms to main problems in protein bioinformatics and molecular biology. A variety of topics, including protein sequence alignments, profiles and protein structure classification and prediction, will be either introduced briefly or discussed in detail. Students will be asked to present some selected research papers. Prerequisite: EECS 730. LEC
View current sections...
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, 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: Graduate standing in CS or CoE or consent of instructor. LEC
View current sections...
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: EECS 730 and EECS 738. LEC
View current sections...
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: Graduate standing in CS or CoE or consent of instructor. LEC
View current sections...
The objective of this course is to give students a hands on introduction to the fundamentals of computer vision. Topics include: Image Formation, Image Segmentation, Binary Image Analysis, Edge Detection, Line Drawing Interpretation, Shape from Shading, Motion Analysis, Stereo, Shape Representation, and Object Recognition. The objective of this course is to give students a hands-on introduction to the fundamentals of computer vision. Prerequisite: EECS 740 or equivalent. LEC
View current sections...
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: EECS 762. LEC
View current sections...
Adaptive filtering, mathematics for advanced signal processing, cost function optimization, signal processing algorithms for optimum filtering and linear prediction, power spectrum estimation, steepest descent, adaptive algorithms. Prerequisite: EECS 744. LEC
View current sections...
Processing requirements for integrated networks and associated applications. Principles of VLSI architectures. Overview of selected network functions, including scrambling and descrambling, synchronization, cell switching, routing, bandwidth shaping and policing, encryption, and decryption. Implementation of network functions using high performance special-purpose architectures. Examples of processors for high speed networks. Prerequisite: EECS 546 and EECS 663. Corequisite: EECS 863. LEC
View current sections...
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: An undergraduate course in probability and statistics, and signal processing. LEC
View current sections...
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: EECS 562. Corequisite: EECS 861. LEC
View current sections...
Modeling and analysis for performance prediction of communication networks. Topics include: an introduction to queueing theory; analysis of TDM systems; modeling and analysis of networks of queues; analysis of congestion and flow control algorithms; analysis of routing algorithms; analysis of bus and ring networks. Prerequisite: EECS 861. LEC
View current sections...
Introduce methodologies for multiwavelength optical network analysis, design, control, and survivability. Prerequisite: EECS 663. LEC
View current sections...
The theory and practice of the engineering of wireless telecommunication systems. Topics include cellular principles, mobile radio propagation (including indoor and outdoor channels), radio link calculations, fading (including Rayleigh, Rician, and other models), packet radio, equalization, diversity, error correction coding, spread spectrum, multiple access techniques (including time, frequency, and code), and wireless networking. Current topics of interest will be covered. Corequisite: EECS 861. LEC
View current sections...
Statistical approaches to processing natural language text have become dominant in recent years. This course is introduction to statistical natural language processing (NLP). The course covers the theory and algorithms needed for building NLP tools. It provides broad but rigorous coverage of mathematical and linguistic foundations, as well as detailed discussion of statistical methods, allowing students to construct their own implementations. Topics include: word sense disambiguation, clustering, text classification, information retrieval, and other applications. Prerequisite: Fluency in programming and knowledge of basic statistics and probability. LEC
View current sections...
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: EECS 862. LEC
View current sections...
Comprehensive coverage of the discipline of high-bandwith low-latency networks and communication, including high bandwidth-x-delay products, with an emphasis on principles, architecture, protocols, and system design. Topics include high-performance network architecture, control, and signalling; 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; end-to-end protocols, mechanisms, and optimizations; and high-bandwidth low-latency applications. Principles will be illustrated with many leading-edge and emerging protocols and architectures. Prerequisite: EECS 563 or EECS 780. LEC
View current sections...
Comprehensive coverage of the disciplines of mobile and wireless networking, with an 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: EECS 563 or EECS 780. LEC
View current sections...
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 the implementation of policy. Issues will be illustrated through laboratories based on common routing platforms. Prerequisite: EECS 745. LEC
View current sections...
Directed studies of advanced phases of electrical engineering, computer engineering, or computer science not covered in regular graduate courses, including advanced laboratory work, special research, or library reading. Prerequisite: Consent of instructor. RSH
View current sections...
Group discussions of selected topics and reports on the progress of original investigations. Prerequisite: Consent of instructor. LEC
View current sections...
A theorem based treatment of electromagnetic theory, with applications. Topics include source modeling, equivalence concepts, Green's functions, construction of solutions, and integral equations. Applications include scattering and electromagnetic numerical techniques. Prerequisite: EECS 720 or equivalent. LEC
View current sections...
Polarimetric plane-wave propagation, including the complex propagation matrix and Stokes vector representation. Electromagnetic scattering, including the scattering matrix, Mueller matrix, scattering cross-section, absorption cross-section, extinction cross-section, Mie scattering, and Rayleigh scattering. Volume scattering in random media, including the Born approximation, Rayleigh scattering statistics, multiple scattering mechanisms, Radiative transfer theory, and volume scattering above a dielectric half-space. Propagation through random media, including the extinction coefficient, the optical theorem, and the distorted Born approximation. Scattering from rough surfaces, including the Kirchoff, Physical Optics and small-perturbation models. Prerequisite: EECS 720. LEC
View current sections...
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: EECS 738, EECS 837, EECS 844 or equivalent. LEC
View current sections...
This course presents the mathematical basis for software that is correct-by-construction. Students will learn basic mathematical techniques for representing, composing and refining software specifications and how they are realized in software systems. Prerequisite: EECS 762 or EECS 755. LEC
View current sections...
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: EECS 861. LEC
View current sections...
A mathematical study of the minimization (or maximization) of functions. The course provides an introduction to the mathematical theory and application of a variety of optimization techniques, with an emphasis on applications related to communication systems. Optimization problem formulation. Unconstrained and constrained minimization, including conditions for optimal points. Specific techniques for solving linear and nonlinear programming problems. Convergence of algorithms. LEC
View current sections...
Mathematical limitations on the generation, storage, and transmission of information. Shannon's first theorem and data-compaction coding. Mutual information. Shannon's second theorem and channel capacity. Information theory and performance limitations of error-correction coding. Rate-distortion theory. Network information theory. Practical applications drawn from telecommunications and other fields. Prerequisite: EECS 862. LEC
View current sections...
Graduate research seminar that provides an overview of the emerging field of resilient, 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: EECS 882; previous experience in simulation desirable. LEC
View current sections...
A study of the principles used by the engineer in managing a technology-based enterprise. Topics include planning, organizing, staffing, directing, and controlling. Prerequisite: Senior or graduate standing in an engineering curriculum or consent of the instructor. LEC
View current sections...
Advanced or experimental work of a specialized nature representing unique or changing needs and resources in engineering management. RSH
View current sections...
This course is intended to introduce the student to the basic concepts of management and motivation for the engineering manager and general behavior of technical organizations. This course presents a history of the schools of management thought through the modern research that began the participative management movement. The course will investigate classical motivational theories and management style principles. The student will perform research to determine how their employer or clients apply these theories. LEC
View current sections...
Applied statistical methods to engineering systems will be introduced in this course for analyzing engineering and management systems. Emphasis will be given to applied regression analysis, analysis of variance, analysis of time dependence by smoothing, Bayes method, time series analysis, auto-regressive moving averages and forecasting model. Prerequisite: Skills in probability, statistics, and computer application. LEC
View current sections...
This course focuses on the impact of technology on society. Techniques of technology forecasting such as Delphi, cross-impact analysis, trend projection, decision trees, and scenarios are discussed. Case studies of technology assessments are presented. Each student is asked to conduct a preliminary technology assessment which is a systematic study of the effects on society which may occur when a technology is introduced or modified. Prerequisite: Elementary skills in statistics, computer programming, and linear algebra. LEC
View current sections...
Principles and theories of business development and marketing as applicable to professional engineering and architectural practices. LEC
View current sections...
Management of technology and technological change through innovation, imitation, and obsolescence; planning, organizing, motivation, and control for innovation; organizational climate and its effects on innovative ideas and entrepreneurship; project/product decisions and R&D strategies in small and large companies; innovation in multinational corporations. LEC
View current sections...
A study of finance including financial planning and management in technological based organizations. Topics covered include financial statement analysis, present value of financial markets, capital budgeting, taxes, investment decisions, replacement decisions, cash flow budgets, and sources of capital. LEC
View current sections...
This course is an introduction to labor relations and human resources, including employment practices in unionized and non-union organizations. The course will examine labor relations, human relations and collective bargaining with emphasis on the negotiation and administration of labor agreements. Included will be a survey of the historical, legal, and structural environments that influence the collective bargaining process. Research topics focus on some of the most important issues in the workplace: protecting jobs, increasing productivity, computerization, worker participation, expanding and declining labor markets, and new methods of decision making in the human resources field. LEC
View current sections...
The overwhelming challenge that faces the U.S. today is the need to regain its competitive position in the world marketplace. This course offers a broad view of Quality Management in that it focuses on the managerial aspects of quality, rather than just the technical. For example, students will learn the Malcolm Baldridge award criteria which focuses on leadership, data analysis, human resources, quality assurance, quality results, and customer satisfaction. In addition, a review of the theory and approaches of the major quality leaders such as Deming, Juran, and Crosby will be covered. Practical applications of TQM concepts in a technological environment will be stressed throughout the course. LEC
View current sections...
Includes the study of theories, tests for, and objectives of engineering and management ethics. Explores personal values. Measures personality profile and preferred communication style for each student. Includes management of stress, time, and career. Each student prepares career and personal development plans. Managerial writing and communication skills are developed through weekly projects including report and proposal preparation, internal correspondence concerning praise and reprimand, and organizational policy preparation. Interpersonal and nonverbal communication styles are studied. Relies heavily on instructor-assisted peer mediation of topics after introduction of constructive techniques of interpersonal communication. LEC
View current sections...
This course emphasizes the use of general system theory, classical optimization and optimality conditions, model development, and theory and application of mathematical programming, to include: linear programming, dynamic programming, queuing models, integer and non-linear programming, and introduction to decision analysis. Prerequisite: Elementary skills in linear algebra, probability, calculus, and computer application. LEC
View current sections...
Methods of developing, implementing, and using computer simulations for management processes such as inventory control, waiting lines, project monitoring, and capital investment decisions are covered. Extensive use is made of simulation languages and interactive graphic-supported gaming and decision analysis. Engineering systems and chemical processes are studied under deterministic and stochastic conditions. Two hours lecture, three hours laboratory per week. LEC
View current sections...
 1 2 3 4 5 6 7 > 

The University of Kansas prohibits discrimination on the basis of race, color, ethnicity, religion, sex, national origin, age, ancestry, disability, status as a veteran, sexual orientation, marital status, parental status, gender identity, gender expression and genetic information in the University’s programs and activities. The following person has been designated to handle inquiries regarding the non-discrimination policies: Director of the Office of Institutional Opportunity and Access, IOA@ku.edu, 1246 W. Campus Road, Room 153A, Lawrence, KS, 66045, (785)864-6414, 711 TTY.