Advanced graduate courses

For more detailed descriptions, syllabi and schedule go to ECE graduate courses page.

  • EC701: Optimal Control and Robust Control. Multivariable poles and zeros, robustness analysis, norms and structured singular values, the Maximum Principle, LQR and LQG control design, robust control design using Loop Transfer Recovery, H-infinity robust design. Cannot be taken for credit in addition to ENG AM764.
  • EC702: Recursive Estimation and Optimal Filtering. State-space theory of dynamic estimation in discrete and continuous time. Linear state-space models driven by white noise, Kalman filtering and its properties, optimal smoothing, non-linear filtering, extended and second-order Kalman filters, and sequential detection. Applications to radar, sonar, and optimal multitarget tracking, parameter identification.
  • EC707: 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.
  • EC708: 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.
  • EC710: 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.
  • EC715:Wireless Communications. Design and analysis of robust wireless communication systems. Spread-spectrum and CDMA. Radio-channel modeling: propagation, path loss, multipath, and fading. Cellular system design. Coding, diversity, and equalization. Alternative communication channels. Case studies. Multiple-access, mobility, and networking issues.
  • EC716: Advanced Digital Signal Processing. Selected topics from time-frequency distributions, parametric signal modeling, high-resolution spectral estimation, multirate signal processing, multidimensional signal processing, adaptive signal processing, alternative algorithms for DFT computation, and signal representation in programs. Application examples chosen from speech, image, sonar, geophysical, and biomedical applications.
  • EC717: 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 n viability of solution methods; problems imaging and computer vision including tomography and surface reconstruction. Computer assignments
  • EC719: 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.
  • EC720: 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.
  • EC724: 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.
  • EC725: 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.
  • EC727: 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.
  • EC733: 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.
  • EC734: 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.
  • EC740: Parameter Estimation and Systems Identification. Application of models with physical parameters to experimental data. Linear and non-linear systems estimation, system identifiability, time and frequency domain estimation, model sensitivity and experiment multivariate statistical analysis, and optimal design. Application predominantly to biomedical systems (e.g., cardiovascular, respiratory, and pharmokinetics). Other applications included. Same as ENG EC 740; students may not receive credit for both.
  • EC741: Randomized Network Algorithms. concepts in probability, graph theory, and algorithms. Tail inequalities and Chernoff bounds. Ball and bins and random graph models. Markov chains and random walks. The probabilistic method. Monte Carlo methods. Introduction to martingales, networking applications: distributed content storage and look-up in P2P networks, IP traceback, fountain codes, universal hash functions, packet routing. Same as SE 741. Students may not receive credit for both.
  • EC744: Mobile Ad Hoc Networking and Computing. Mobile routers, wireless interconnectivity, and an unpredictably changing topology characterize a Mobile Ad hoc Network (MANET). Covers MANET-specific topics related to resource discovery, handoff, MAC-layer, security, routing, mobility and location management, self-organization, caching, and practical implementations.
  • EC749: Interconnection Networks fo Multicomputers. Interconnection network topologies. Static and dynamic networks. Routing in multicomputer networks. Network flow control. Deadlocks in routing. Multicast and broadcast. Fault-tolerance and reliability of interconnection networks. Modules for realization (nodes and routers). Performance metrics for different topologies.