Courses

The listing of a course description here does not guarantee a course’s being offered in a particular semester. Please refer to the published schedule of classes on the Student Link for confirmation a class is actually being taught and for specific course meeting dates and times.

• ENG EC 707: Radar Remote Sensing
  Principles of radar systems and radar signal analysis with emphasis on environmental remote sensing. Topics include antenna fundamentals, wave propagation/scattering in various media, the radar equation, radar cross-section, target characteristics, ambiguity function, radar system components, pulse compression techniques, and aperture synthesis. Highlighted systems include ground-penetrating radars, synthetic aperture radar (SAR), weather radars, and incoherent scatter radars, and LIDAR.
• ENG EC 708: Advanced Process Control
  Integrated study of process control and modern control theory. Includes process modeling and simulation, analysis of linear and non-linear dynamics, evaluation and selection of actuators and measurements, control structure design for single and multiple variable systems, and control algorithm design. Examples drawn from a variety of process control applications. Same as MN 508, students may not receive credit for both.
• ENG EC 710: Dynamic Programming and Stochastic Control
  Introduction to sequential decision making via dynamic programming. The principle of optimality as a unified approach to optimal control of dynamic systems and Markovian decision problems. Applications from control theory and operation research include linear-quadratic problems, the discrete Kalman Filter, inventory control, network, investment, and resource allocation models. Adaptive control and numerical solutions through successive approximation and policy iteration, suboptimal control, and neural network applications involving functional approximations and learning. Meets with ENGME710 and ENGSE710. Students may not receive credit for both.
• ENG EC 712: Advanced Software for Computer Engineers
  Explores the design of software using state-of-the-art technologies; emphasis on distributed systems, Web-based applications, and the use of the latest application frameworks; project-oriented course.
• ENG EC 713: Parallel Computer Architecture
  Problems in parallel processing, how they are addressed by current parallel computers, and design of future systems. Topics include characteristics of parallel applications; parallel system support; cache coherency protocols; network interfaces; switch and interconnection network design; scalable systems; and hardware-software tradeoffs. Examples of both small-scale and large-scale parallel systems, including web servers, clusters of networked PCs, MPPs, and vector supercomputers.
• ENG EC 715: Wireless Communications
  Design and analysis of robust wireless communication systems. Radio-channel modeling: propagation, path loss, multipath, and fading. Cellular system design. Coding, diversity, and equalization. Multi-antenna channels, Multicarrier modulations, Spread-spectrum and CDMA techniques. Multiuser scheduling. Case studies. Multiple-access, mobility, and networking issues.
• ENG EC 716: Advanced Digital Signal Processing
  Selected topics from time-frequency distributions, parametric signal modeling, high-resolution spectral estimation, multi-rate signal processing, multidimensional signal processing, adaptive signal processing, alternative algorithms for DFT computation, symbolic and knowledge based signal processing. Application examples chosen from speech, image, communication, and biomedical applications.
• ENG EC 717: Image Reconstruction and Restoration
  Principles and methods of reconstructing images and estimating multidimensional fields from indirect and noisy data; general deterministic (variational) and stochastic (Bayesian) techniques of regularizing ill-posed inverse problems; relationship of problem structure (data and models) to computational efficiency; impact of typically large image processing problems on viability of solution methods; problems in imaging and computational vision including tomography and surface reconstruction. Computer assignments.
• ENG EC 719: Statistical Pattern Recognition
  The statistical theory of pattern recognition, including both parametric and nonparametric approaches to classification. Covers classification with likelihood functions and general discriminant function, density estimation, supervised and unsupervised learning, decision trees, feature reduction, performance estimation, and classification using sequential and contextual information, including Markov and hidden Markov models. A project involving computer implementation of a pattern recognition algorithm is required.
• ENG EC 720: Digital Video Processing
  Review of sampling/filtering in multiple dimensions, human visual system, fundamentals of information theory. Motion analysis: detection, estimation, segmentation, tracking. Image sequence segmentation. Spectral analysis of image sequences. Video enhancement: noise reduction, super-resolution. Video compression: transformation, quantization, entropy coding, error resilience. Video compression standards (H.26X and MPEG families). Future trends in image sequence compression and analysis. Homework and project will require MATLAB programming.
• ENG EC 724: Advanced Optimization Theory and Methods
  Introduces advanced optimization techniques. Emphasis on nonlinear optimization and recent developments in the field. Topics include: unconstrained optimization methods such as gradient, conjugate direction, Newton and quasi-Newton methods; constrained optimization methods such as gradient projection, feasible directions, barrier and interior point methods; duality theory and methods; convex duality; and introduction to other advanced topics such as semi-definite programming, incremental gradient methods and stochastic approximation algorithms. Applications drawn from control, production and capacity planning, resource allocation, communication and neural network problems. Meets with ENGME724 and ENGSE724. Students may not receive credit for both.
• ENG EC 725: Queueing Systems
  Performance modeling using queueing networks analysis of product form and nonproduct form networks, numerical methods for performance evaluation, approximate models of queueing systems, optimal design and control of queueing networks. Applications from manufacturing systems, computer systems, and communication networks. Meets with ENGME725 and ENGSE725. Students may not receive credit for both.
• ENG EC 726: Personal Knowledge Engineering
  Introduction to concepts and methods of Knowledge Engineering on a personal scale. Aimed at students who foresee the need to structure and activate information on their own terms in research, business, authoring, presence on the Internet, etc., or do original research in that area. Includes expressing tasks, processes, and documents in terms of essential features and goals, and how to let computers translate this ?deep structure? into the ?surface expression? appropriate to a desired use. Specifically, how to create ?personal agents? to extend the reach in various directions (memory enhancement, Web mining, and task automation). Among the methodological issues to be treated: semantic tagging (e.g., XML) vs. informal structuring; Markovian vs. Bayesian search methods; making the design/fabricate/evaluate cycle accessible to the layman; scripting language as a personal servant.
• ENG EC 727: Advanced Coding Theory
  Advanced topics in the theory of error-correcting codes, with an emphasis on decoding algorithms. Various codes and corresponding decoding algorithms: cyclic (BCH, Reed-Solomon), Reed-Muller, Golay, algebraic-geometry (Goppa, Hermitian), and iteratively-decoded codes (turbo and LDPC), graph-based decoding; trellis construction and decoding (Viterbi algorithm), belief propagation (sum-product, min-sum). Various applications: cryptography, data synchronization, and tiling.
• ENG EC 728: Design and Testing for Distributed Software-Intensive Systems
  Systems and software requirements definition, architectural software design, object-oriented software development and testing, with emphasis on distributed software-intensive systems (i.e., software for telecommunications, real-time control systems, etc.) Individual project involving requirements definition and a team project involving object-oriented software architecture, design and testing.
• ENG EC 730: Information-Theoretical Design of Algorithms
  Recently developed information-theoretical approach to the analysis and design of computer algorithms. Previous knowledge of information theory or the theory of algorithms is not required, though desirable. Main topics include the complexity of algorithms; P, E, NP, and NP?hard problems; basic concepts of information theory, optimal coding; information-theoretical approach to sorting, order statistics, binary search, decision trees, hashing, minimization of Boolean functions, test, and similar problems; and design of efficient computer algorithms.
• ENG EC 731: Applied Plasma Physics
  Statistical description of plasmas as many-body systems. Liouville equation. Distribution functions. Transport phenomena in plasmas. Fokker-Planck theory. Applications for MHD power generation, sputtering, plasma deposition, ambipolar diffusion in machine plasmas. Kinetic equations for plasma. Maxwell-Vlasov theory of plasma waves and plasma instability. Applications to microwave devices, particle beams, space and laboratory plasmas. Fluctuations, correlations, and plasma radiation.
• ENG EC 732: Combinatorial Optimization and Graph Algorithms
  of algorithms for the solution of optimization problems with discrete decision spaces. Review of linear programming and duality. Discussion of advanced network optimization algorithms and matroid optimization. Approximate algorithms for NP-Hard optimization problems. Submodular optimization. Meets with ENGSE732. Students may not receive credit for both.
• ENG EC 733: Discrete Event and Hybrid Systems
  Review of system theory fundamentals distinguishing between time-driven and event-driven dynamics. Modeling of Discrete Event and Hybrid Systems: Automata, Hybrid Automata, Petri Nets, basic queueing models, and stochastic flow models. Monte Carlo computer simulation: basic structure and output analysis. Analysis, control and optimization techniques based on Markov Decision Process theory with applications to scheduling, resource allocation and games of chance. Perturbation Analysis and Rapid Learning methods with applications to communication networks, manufacturing systems, and command-control. Meets with ENGME733 and ENGSE733. Students may not receive credit for both.
• ENG EC 734: Hybrid Systems
  The course offers a detailed introduction to hybrid systems, which are dynamical systems combining continuous dynamics (modeled by differential equations) with discrete dynamics (modeled by automata). The covered topics include modeling, simulation, stability analysis, verification, and control of such systems. The course contains several applications from both natural and manmade environments, ranging from gene networks in biology, to networked embedded systems in avionics and automotive controls, and to motion planning and control in robotics. Same as ENG ME 734 and ENG SE 734. Students may receive credit for one.

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