Electrical & Computer Engineering

Courses

ECE 501 Topics in Circuits and Systems 3.0 Credits

Circuit laws, transfer functions, convolution, transform techniques, systems engineering. This series of courses may be used to meet the admission prerequisites to ECE graduate program. One credit per term is creditable to the M.S.E.E. degree.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit

ECE 502 Topics In Communications, Controls and Computers 3.0 Credits

Modulation theory, noise, feedback theory, stability, computer engineering fundamentals, computers in communication and controls. This series of courses may be used to meet the admission prerequisites to the ECE graduate program. One credit per term is creditable to the M.S.E.E. degree.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit

ECE 503 Topics in Mathematical Techniques In Electrical and Computer Engineering 3.0 Credits

Complex variables in communication and control, matrix methods in circuits and systems, vector calculus in fields, two-dimensional image processing. This series of courses may be used to meet the admission prerequisites to the ECE graduate program. One credit per term is creditable to the M.S.E.E. degree.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit

ECE 531 Modern Transistors 3.0 Credits

This course teaches the underlying physics of the operation of modern bipolar and unipolar transistors which are used in modern electronics. This background is helpful for a) courses related to digital microelectronics, logical gates, memories, and sub circuits, and VLSI circuits; b) courses in analog electronics; and c) courses in microwave electronic systems.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit

ECE 532 Modern Photonics 3.0 Credits

This course will teach students the principles that underline the interaction of light and matter, leading to the understanding of the basis of operation of photonic devices such as lasers, LEDs, solar cells, and photodetectors. The course starts with how understanding of light spectrum that is generated due to heat started the development of the field of quantum mechanics by Max Planck. This is then expanded by Einstein to include a quantum theory of light, on which basis absorption, stimulated and spontaneous emission are explained. Building on that work, we analyze light interaction with semiconductors and show how lasers, LEDs and photodetectors work, and how modern photonics is able to solve great challenges of humanity.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit

ECE 571 Introduction to Electrical and Computer Engineering Research 0.0 Credits

Topics of departmental research. Thesis selection. Required of all full-time graduate students.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit

ECE 572 Techniques of Electrical and Computer Engineering Research 0.0 Credits

Techniques for making technical presentations: oral and written modes. Meeting organization, audience awareness. Writer-to-reader communication. Required of all full-time graduate students.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit

ECE 573 Presentation of Electrical and Computer Engineering Research 0.0 Credits

Conference attendance and critique. Student presentation and critique. Topics of concern: professional ethics, liability, etc. Required of all full-time graduate students.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit

ECE 603 Computing and Control 3.0 Credits

This course focuses on the practical aspects of implementing Computer Control using microcontrollers in such applications as: Automated Equipment, Robotics, Motor Control, Process Control and Aerospace. The course is essentially divided into two parts: (1) the computer in the loop and (2) addressing noisy measurements.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit

ECE 610 Machine Learning & Artificial Intelligence 3.0 Credits

This course introduces students to topics in modern machine learning, along with applications of machine learning to problems in engineering. Introductory topics will include an overview of classification, overfitting, cross-validation, and dimensionality reduction. Supervised classification approaches will be covered including linear classifiers, generative and discriminative models, non-probabilistic classification approaches, kernel methods, and neural networks. Topics in unsupervised learning will also be covered if time permits.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit
Prerequisites: ECES 521 [Min Grade: C]

ECE 612 Applied Machine Learning Engineering 3.0 Credits

This course emphasizes how to gather data then train, test, and deploy practical machine learning systems using modern software libraries, with an emphasis on Keras on TensorFlow. Complementing the other department courses emphasizing the mathematics behind machine learning algorithms and the ways these can be tailored to specific computing architectures, this project-focused course emphasizes the practice of rapidly prototyping and testing multiple learning structures. To provide the broadest applicability, datasets will range from rich text, to financial time series, to sound, images, and video.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit

ECE 613 Neuromorphic Computing 3.0 Credits

This course will cover the principles of neuromorphic computing. Topics will cover 1) fundamentals of spiking neural network (SNN), which mimics the computation in mammalian brain; 2) supervised and unsupervised learning algorithms for SNN; 3) novel applications of SNN, including in vision and time series processing; 4) architectures for implementing SNN in hardware, aka neuromorphic hardware; 5) introduction to non-volatile memory technologies to implement synaptic processing in neuromorphic hardware; 6) software stacks for neuromorphic computing; and 7) design challenges in dependable neuromorphic computing.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit

ECE 630 Software Defined Radio Laboratory 3.0 Credits

This laboratory course takes a Software-Defined Radio (SDR) implementation approach to learn about modern analog and digital communication systems. Software defined radio uses general purpose radio hardware that can be programmed in software to implement different communication standards. Discussion of the basic principles of wireless radio frequency transmissions and leverage this knowledge to build analog and digital communication systems. Knowledge of these techniques and systems will provide a platform that can be used in the class project for further exploration of wireless networking topics such as cybersecurity, cognitive radio, smart cities, and the Internet of Things.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit

ECE 686 Cell & Tissue Image Analysis 3.0 Credits

Theory and practice of building computational tools for biological image analysis.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit

ECE 687 Pattern Recognition 3.0 Credits

Theory of supervised and unsupervised statistical pattern recognition, presented through practical programming techniques.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit

ECE 695 Research Rotations in Cybersecurity 1.0-12.0 Credit

The research rotation course allows students to gain exposure to cybersecurity-related research that cuts across conventional departmental barriers and traditional research groups, prior to identifying and focusing on a specific interdisciplinary project or thesis topic. Students selecting to participate in research rotations would participate in the research activities of two labs for each three credits of research rotation they undertake.

College/Department: College of Engineering
Repeat Status: Can be repeated multiple times for credit

ECE 697 Research 1.0-12.0 Credit

Research in electrical and computer engineering.

College/Department: College of Engineering
Repeat Status: Can be repeated multiple times for credit

ECE 898 Master's Thesis 1.0-12.0 Credit

Master's thesis in electrical and computer engineering.

College/Department: College of Engineering
Repeat Status: Can be repeated multiple times for credit

ECE 997 Dissertation Research 1.0-12.0 Credit

Graded Ph.D. dissertation research in electrical and computer engineering.

College/Department: College of Engineering
Repeat Status: Can be repeated multiple times for credit

ECE 998 Ph.D. Dissertation 1.0-12.0 Credit

Ph.D. dissertation research in electrical and computer engineering.

College/Department: College of Engineering
Repeat Status: Can be repeated multiple times for credit

ECE I699 Independent Study in ECE 0.0-12.0 Credits

Self-directed within the area of study requiring intermittent consultation with a designated instructor.

College/Department: College of Engineering
Repeat Status: Can be repeated multiple times for credit

ECE T580 Special Topics in ECE 0.0-12.0 Credits

Topics decided upon by faculty will vary within the area of study.

College/Department: College of Engineering
Repeat Status: Not repeatable for credit

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