This course explores advanced embedded systems topics such as design and validation of embedded computing systems, embedded C programming, real-time operating systems for microcontrollers, safety and security, cyber-physical systems, Internet of Things, and robotics. The course includes hands-on experience, paper presentations, and discussions.  Prerequisite: ECE 3430

This is a survey course in the theory and technology of modern wireless communication systems, exemplified in cellular telephony, paging, microwave distribution systems, wireless networks, and even garage door openers. Wireless technology is inherently interdisciplinary, and the course seeks to serve the interests of a variety of students.

Under faculty supervision, students plan a project of at least one semester's duration, conduct the analysis or design and test, and report on the results. If this work is to be the basis for an undergraduate thesis, the course should be taken no later than the seventh semester. Prerequisite: Instructor permission.

Quantum electronics, the study of light and matter interaction, has become the cornerstone in many areas of optical science and technology. This course reviews the principles of lasers then introduces the generalized nonlinear wave equations. This course will cover typical nonlinear effects and their applications in telecommunication, ultrafast laser, quantum computing/information and chemical/bio spectroscopy.

Explores measurement and behavior of high-frequency circuits and components. Equivalent circuit models for lumped elements. Measurement of standing waves, power, and frequency. Use of vector network analyzers and spectrum analyzers. Computer-aided design, fabrication, and characterization of microstrip circuits. Corequisite: ECE 5260 or instructor permission.

This one-hour weekly seminar course features presentations given by ECE faculty members, to introduce various research areas, topics, and advances in Electrical and Computer Engineering. This course is required for all first-year ECE graduate students. 

This course introduces students to the key concepts in convex optimization theory with the goal of enabling them to formulate and solve various convex optimization problems arising in engineering, data science, and machine learning. Non-convex optimization techniques in deep learning will also be introduced.

Detailed study of graduate course material on an independent basis under the guidance of a faculty member.

A guided teaching experience for Ph.D. students, with selected teaching assignments and directed performance evaluation, under the supervision of a faculty member, as a part of Ph.D. training designed for students' development of independent teaching skills.

An in-depth treatment of digital communications techniques and performance. Topics include performance of uncoded systems such as Mary, PSK, FSK, and multi-level signaling; orthogonal and bi-orthogonal codes; block and convolutional coding with algebraic and maximum likelihood decoding; burst correcting codes; efficiency and bandwidth; synchronization for carrier reference and bit timing; baseband signaling techniques; intersymbol interference; and equalization. Prerequisite: ECE 6711.