Program Core (12 Credits)
EECS 442 Computer Vision
Prerequisites: EECS 281 or graduate standing. Alternate years 4 credits
Computational methods for the recovery, representation, and application of visual information. Topics from image formation, binary images, digital geometry, similarity and dissimilarity detection, matching, curve and surface fitting, constraint propagation, relaxation labeling, stereo, shading texture, object representation and recognition, dynamic scene analysis, and knowledge based techniques. Hardware, software techniques.
EECS 461 Embedded Control Systems
Prerequisites: EECS 216 or EECS 306 or EECS 373 or graduate standing. I 4 credits
Basic interdisciplinary concepts needed to implement a microprocessor-based control system. Sensors and actuators. Quadrature decoding. Pulse width modulation. DC motors. Force feedback algorithms for human computer interaction. Real time operating systems. Networking. Use of MATLAB to model hybrid dynamical systems. Autocode generation for rapid prototyping. Lecture and laboratory.
ME 552 Mechatronic Systems Design
Prerequisite: ME 350, ME 360, EECS 314 or equivalent 3 credits
Mechatronics is the synergistic integration of mechanical disciplines, controls, electronics and computers in the design of high-performance systems. Case studies, hands-on lab exercises and hardware design projects cover the practical aspects of machine design, multi-domain systems modeling, sensors, actuators, drives circuits, simulation tools, DAQ, and controls implementation using microprocessors.
ME/EE 567 Introduction to Robotics
Prerequisite: graduate standing or permission of instructor 3 credits
Introduction to the central topics in robotics, including geometry, kinematics, differential kinematics, dynamics, and control of robot manipulators. The mathematical tools required to describe spatial motion of a rigid body will be presented in full. Motion planning including obstacle avoidance is also covered.
NA 590/RAV 501, Introduction to Mobile Rockets
Sensing, Perception and Cognition
EECS 542 Vision Processing
Prerequisite: EECS 442. Alternate years 3 credits
Details of image formation theory, including the consideration of dynamic image sequences. The theoretical frameworks for edge detection, feature extraction, and surface description are presented. The relationship between image formation and object features is examined in detail. Programming required.
EECS 644 (PSYCH 644) Computational Modeling of Cognition
Prerequisite: graduate standing or permission of instructor. II Alternate years 2-4 credits
This course will examine computational models of human cognitive processes. Course goals include learning about important computational models of specific cognitive domains and evaluating the appropriateness and utility of different computational approaches to substantive problems in cognition.
IOE 633 Man Machine Systems
NAME 477 Principles of Virtual Reality
RAV 521 Sensing and Sensors
Intelligence and Learning
EECS 492 Introduction to Artificial Intelligence
Prerequisite: EECS 281 or graduate standing. I, II 4 credits
Fundamental concepts of AI, organized around the task of building computational agents. Core topics include search, logic, representation and reasoning, automated planning, decision making under uncertainty, and machine learning.
EECS 543 Knowledge-Based Systems
Prerequisite: EECS 281 and graduate standing or permission of instructor. I 3 credits
Techniques and principles for developing application software based on explicit representation and manipulation of domain knowledge, as applied to areas such as pattern matching, problem-solving, automated planning, and natural-language processing. Discussion of major programming approaches used in the design and development of knowledge-based systems.
EECS 545 Machine Learning
Prerequisite: EECS 492 3 credits)
Survey of recent research on learning in artificial intelligence systems. Topics include learning based on examples, instructions, analogy, discovery, experimentation, observation, problem-solving and explanation. The cognitive aspects of learning will also be studied.
EECS 592 Advanced Artificial Intelligence
Prerequisite: EECS 492 or permission of instructor. II 4 credits
Advanced topics in artificial intelligence. Issues in knowledge representation, knowledge-based systems, problem solving, planning and other topics will be discussed. Students will work on several projects.
EECS 594 Introduction to Adaptive Systems
Prerequisite: EECS 203, MATH 425 (Stat 425). Alternate years 3 credits
Programs and automata that "learn" by adapting to their environment; programs that utilize genetic algorithms for learning. Samuel's strategies, realistic neural networks, connectionist systems, classifier systems, and related models of cognition. Artificial intelligence systems such as NETL and SOAR are examined for their impact upon machine learning and cognitive science.
EECS 692 Special Topics in Artificial Intelligence
Prerequisites: permission of instructor. 3 credits
Current topics of interest in artificial intelligence. This course can be repeated for credit.
Information and Signal Processing
AERO 450 Flight Software Systems
Prerequisites: ENGR 101 and AEROSP 245. I 3 credits
Theory and practice of embedded flight software systems. Computational theory topics include discrete mathematics, finite automata, computational complexity, and model checking. Software development concepts include object-oriented programming, networks, multi-threaded software, real-time scheduling, and sensor/actuator interface protocols. Emphasis placed on C/C++ development in Linux with guidance, navigational control applications. Lectures and laboratory.
AERO 586 Aerospace Information Systems
EECS 501 Probability and Random Processes
Prerequisite: EECS 401 or graduate standing. I, II 4 credits
Introduction to probability and random processes. Topics include probability axioms, sigma algebras, random vectors, expectation, probability distributions and densities, Poisson and Wiener processes, stationary processes, autocorrelation, spectral density, effects of filtering, linear least-squares estimation, and convergence of random sequences.
EECS 551 Mathematical Methods for Signal Processing
Prerequisite: Preceded or accompanied by EECS 501. I 3 credits
Linear shift-invariant systems in continuous time and discrete time. Sampling theory. Fourier analysis. Sample rate conversion. Signal representation in vector spaces. Projection theorem and least-squares approximations. Eigendecompositions and signal subspace methods. Applications in signal processing.
EECS 556 Image Processing
Prerequisite: EECS 501, EECS 551. II 3 credits
Theory and application of digital image processing. Random field models of images. Sampling, quantization, image compression, enhancement, restoration, segmentation, shape description, reconstruction of pictures from their projections, pattern recognition. Applications include biomedical images, time-varying imagery, robotics, and optics.
EECS 559 Advanced Signal Processing
Prerequisite: EECS 551 and EECS 501. I 3 credits
Estimators of second order properties of random processes: nonparametric and model-based techniques of spectral estimation, characterization of output statistics for nonlinear systems, time-frequency representations. Performance evaluation using asymptotic techniques and Monte Carlo simulation. Applications include speech processing, signal extrapolation, multidimensional spectral estimation, and beamforming.
EECS 571 Principles of Real-Time Computing
Prerequisite: EECS 470, EECS 482 or permission of instructor. I 4 credits
Principles of real-time computing based on high performance, ultra reliability and environmental interface. Architectures, algorithms, operating systems and applications that deal with time as the most important resource. Real-time scheduling, communications and performance evaluation.
IOE 515 Stochastic Processes
Prerequisite: IOE 316 or Stats 310. I 3 credits
Introduction to non-measure theoretic stochastic processes. Poisson processes, renewal processes, and discrete time Markov chains. Applications in queueing systems, reliability, and inventory control.
Dynamics and Control
AERO 572 Dynamics and Control of Aircraft
AERO 740 Special Topics in Flight Dynamics and Control Systems
(to be arranged)
EECS 598 Special Topics in Electrical Engineering and Computer Science
Prerequisite: permission of instructor or counselor. I, II, IIIa, IIIb, and III 1-4 credits
Topics of current interest in electrical engineering and computer science. Lectures, seminar, or laboratory. Can be taken more than once for credit.
ME 540 (AERO 540). Intermediate Dynamics
Prerequisite: ME 240. I or II 3 credits
Newton/Euler and Lagrangian formulations for three dimensional motion of particles and rigid bodies. Principles of dynamics applied to various rigid-body and multi-body dynamics problems that arise in aerospace and mechanical engineering.
ME 542 Vehicle Dynamics
Prerequisite: ME 440. II 3 credits
Dynamics of the motor vehicle. Static and dynamic properties of the pneumatic tire. Mechanical models of single and double-track vehicles enabling prediction of their response to control forces/moments and external disturbances. Directional response and stability in small disturbance maneuvers. The closed-loop driving process. Behavior of the motor vehicle in large perturbation maneuvers. Ride phenomena treated as a random process.
ME 561 (EECS 561) Design of Digital Control Systems
Prerequisite: EECS 460 or ME 461. I, II 3 credits
Sampling and data reconstruction. Z-transforms and state variable descriptions of discrete-time systems. Modeling and identification. Analysis and design using root locus, frequency response, and state space techniques. Linear quadratic optimal control and state estimation. Quantization and other nonlinearities.
ME 568 Vehicle Control Systems
Prerequisite: ME 461 or equivalent. I 3 credits
Design and analysis of vehicle control systems such as cruise control, traction control, active suspensions and advanced vehicle control systems for Intelligent Vehicle-Highway Systems (IVHS). Human factor considerations such as driver interfaces. This course may be used as part of the IVHS certification program.
AERO 565 Optimal Structural Design
Prerequisite: AERO 315, a course in advanced calculus. II 3 credits
Optimal design of structural elements (bars, trusses, frames, plates, sheets) and systems; variational formulation for discrete and distributed parameter structures; sensitivity analysis; optimal material distribution and layout; design for criteria of stiffness, strength, buckling, and dynamic response.
ME 452 (MFG 452) Design for Manufacturability
Prerequisite: ME 350 I 3 credits
Conceptual design. Design for economical production, Taguchi methods, design for assembly; case studies. Product design using advanced polymeric materials and composites; part consolidation, snap-fit assemblies; novel applications. Design projects.
ME 551 (MFG 560) Mechanisms Design
Prerequisite: ME 350 II 3 credits
Basic concepts. Type synthesis - creative design of mechanisms; graph theory. Precision-point Burmester theory for dimensional synthesis of linkages. Applications. Cam and follower system synthesis. Joint force analysis and dynamic analysis formulations. Analytical synthesis of programmable and compliant mechanisms. Use of software for synthesis and analysis. Design projects.
ME 555 (MFG 555) Design Optimization
Prerequisite: Math 451 and Math 217 or equivalent. II 3 credits
Mathematical modeling of engineering design problems for optimization. Boundedness and monotonicity analysis of models. Differential optimization theory and selected numerical algorithms for continuous nonlinear models. Emphasis on the interaction between proper modeling and computation. Students propose design term projects from various disciplines and apply course methodology to optimize designs.
ME 559 (MFG 559) Smart Materials and Structures
Prerequisite: EECS 314 or equivalent. I alternate years 3 credits
This course will cover theoretical aspects of smart materials, sensors and actuator technologies. It will also cover design, modeling and manufacturing issues involved in integrating smart materials and components with control capabilities to engineering smart structures.
Management and Systems
CEE 586 (Nat Res 557) Industrial Ecology
Prerequisite: senior standing. II 3-4 credits
Analysis of material and energy flows in industrial systems to enhance eco-efficiency and sustainability. Methods: life cycle assessment quantifies energy, waste, emissions (greenhouse gases) for materials production, manufacturing, product use, recovery/disposition. Life cycle design integrates environmental, performance, economic, and regulatory objectives. Multi-objective analysis, engineering design analysis, cross-functional teamwork, large sea modeling skills.
CEE 589 (Nat Res 595) Risk and Benefit Analysis in Environmental Engineering
Prerequisite: senior or graduate standing. I 3 credits
Introduction to techniques of risk-benefit analysis as applied to water resources and environmental engineering. Techniques of multi-objective water resource planning. The engineering political interfaces; consideration of political bargaining and decision-making.
EECS 495 Patent Fundamentals for Engineers
EECS 498 Special Topics
Prerequisite: permission of instructor. 1-4 credits
Topics of current interest selected by the faculty. Lecture, seminar or laboratory.
EIH 572 Environmental Impact Assessment
ES 715 Driving the Innovation Process
MFG 599A Special Topics, Financial Analysis for Modern Manufacturing
Prerequisite: see individual department requirements. I, II, IIIa, IIIb, III 3 credits