ECE Courses

  • Click on the course number for a detailed course outline.
Course Number  Course Title and Catalog Description
Engineering Software Design
Object-oriented software methods for engineering applications. Numerical analysis methods; simulations and graphical presentation of simulation results; analysis of numerical precision. Programming projects.
Signals and Systems
Continuous-time linear systems and signals, their mathematical representations, and computational tools; Fourier and Laplace transforms, convolutions, input-output responses, stability.
Software Fundamentals for Engineering Systems
Using computer algorithms for solving electrical engineering problems arising in various application domains. Development of effective algorithms and their implementation by object-oriented code.
Feedback Control Systems
Analysis and design of control systems. Laplace transforms, transfer functions, and stability. Feedback systems: tracking and disturbance rejection. Graphical design techniques.
Control System Design
Design of control algorithms using state-space methods, microcontroller implementation of control algorithms in C, and laboratory projects emphasizing motion control applications.
Embedded and Hybrid Control Systems
Modeling, analysis, and design of embedded and hybrid control systems.
Introduction to Automation and Robotics
Concurrent engineering principles; robotic manipulator kinematics, dynamics and control; applications of robots in industry, medicine and other areas; team projects and hands-on laboratory experience.
Neural Networks and Fuzzy Logic in Control
Principles of neural networks and fuzzy systems; the MATLAB Neural Network and Fuzzy Logic Toolboxes; examples from system identification, classification and control; laboratory experience.
Game Theory and Multiagent Systems
An introduction to game theory and its application to multiagent systems, including distributed routing, multivehicle control, and networked systems.
System Theory for Communication and Control
Study of the basic concepts in linear system theory and numerical linear algebra with applications to communication, compution, control and signal processing. A unified treatment.
Computatonal Computer Vision
Computational and theoretical aspects of computer vision. Application areas include robotics, autonomous vehicles, tracking, and image-guided surgery. Includes major project.
Industrial Controls and Manufacturing
Students are introduced to industrial controls and the fundamentals of manufacturing with hands-on experience based on lab projects using industry software and hardware for communications and control. Crosslisted with TFE 4761.
Linear Systems and Controls
Introduction to linear system theory and feedback control. Topics include state space representation, controllability and observability, linear feedback control.
Digital Control
Techniques for analysis and synthesis of computer-based control systems. Design projects provide an understanding of the application of digital control to physical systems.
Nonlinear Systems and Control
Classical analysis techniques and stability theory for nonlinear systems. Control design for nonlinear systems, including robotic systems. Design projects.
Optimal Control and Optimization
Optimal control of dynamic systems, numerical optimization techniques and their applications in solving optimal-trajectory problems.
Adaptive Control
Methods of parameter estimation and adaptive control for systems with constant or slowly-varying unknown parameters. MATLAB design projects emphasizing applications to physical systems.
Optimal Estimation
Techniques for signal and state estimation in the presence of measurement and process noise with the emphasis on Wiener and Kalman filtering.
Intelligent Control
Principles of intelligent systems and their utility in modeling, identification and control of complex systems; neuro-fuzzy tools applied to supervisory control; hands-on laboratory experience.
Manufacturing Systems Design
Analytic and simulation tools for design, control and optimization of manufacturing systems. Discrete event dynamic systems and optimization.
Stochastic Systems
Advanced techniques in stochastic analysis with emphasis on stochastic dynamics, nonlinear filtering and detection, stochastic control and stochastic optimization and simulation methods.
Advanced Linear Systems
Study of multivariable linear system theory and robust control design methodologies.
Advanced Computer Vision & Image Processing using PDEs and Active Contours
Algorithms for computer vision and image processing, emphasizing partial-differential equation and active contour methods. Topics include image smoothing and enhancement, edge detection, morphology, and image reconstruction.
Computing for Control Systems
Introduction to real-time computing, distributed computing, and software engineering in control systems. The particular requirements of control systems will be presented.
Autonomous Control of Robotic Systems
Fundamental issues associated with autonomous robot control. Emphasizes biological perspective that forms the basis of many current developments in robotics.
Networked Control and Multiagent Systems
Covers tools and techniques for networked control systems as well as application domains and promising research directions.