Provides first-hand exposure to communications practice, including response of systems, signal theory, modulation and detection, sampling and quantization, digital signal processing, and receiver design. Prerequisite: ECE 3760; corequisite: ECE 4710.

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.

This course will teach students the required skills, concepts, and algorithms to develop mobile robots that act autonomously in complex environments. The main emphasis is on mobile robot locomotion and kinematics, control, sensing, localization, mapping, path planning, and motion planning. Besides theory, students are exposed to simulation environments and lab exercises with real robotic systems.

Today's electronic devices are reaching nanometer dimensions where fundamental quantum and atomistic processes dominate. Instead of the traditional 'top-down' classical viewpoint in "Solid State Device" courses, quantum transport principles are needed to understand `bottom-up' how current flows through individual atoms, molecules, nanotubes or spintronic devices. This course provides a convenient starting point.

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 course explores the intricacies of AI hardware, including the current landscape and anticipating the necessary developments in response to AI's rapid growth and widespread integration across all computing tiers. Through this exploration, you will gain an understanding of both the existing technologies and the future challenges in AI hardware design and implementation.

Focuses on techniques for designing and analyzing dependable computer-based systems. Topics include basic dependability concepts and attributes, fault models and effects, combinatorial and state-space modeling, hardware redundancy, error detecting and correcting codes, time redundancy, software fault tolerance, checkpointing and recovery, reliable networked systems, error detection techniques, and experimental dependability evaluation techniques.Prerequisites: A basic knowledge of probability and computer architecture is required. A working knowledge of programming is required for homework and mini projects.

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.  It is a one-credit course required for all first-year ECE graduate students. 

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