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.

Integration of computer organization concepts such as data flow, instruction interpretation, memory systems, interfacing, and microprogramming with practical and systematic digital design methods such as behavioral versus structural descriptions, divide-and-conquer, hierarchical conceptual levels, trade-offs, iteration, and postponement of detail.  Design exercises are accomplished using a hardware description language and simulation.  Prerequisite by topic:  Digital Logic Design (ECE 2330 or equivalent), Introductory Computer Architecture (ECE 3330 or equivalent), Assembly Language Programming.

Reviews the electromagnetic principles of optics; Maxwell's equations; reflection and transmission of electromagnetic fields at dielectric interfaces; Gaussian beams; interference and diffraction; laser theory with illustrations chosen from atomic, gas and semiconductor laser systems; detectors including photomultipliers and semiconductor-based detectors; and noise theory and noise sources in optical detection. Prerequisite: ECE 3103, 3209, 3750.

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 aims to provide an instruction to basic principles and tools for the analysis and design of control systems. It is intended for general graduate students in engineering and science. Topics to be covered include concepts, examples and designs of feedback, system modeling, linear and nonlinear dynamic behaviors, stability analysis, frequency domain analysis and design, transfer functions, PID control, and robustness of control systems.

This course focuses on an in-depth study of advanced topics and interests in image data analysis. Students will learn practical image techniques and gain mathematical fundamentals in machine learning needed to build their own models for effective problem solving. The graduate students (ECE/CS 6501) will be given additional programming tasks and more advanced theoretical questions.

Studies the modeling, analysis, design, computer simulation, and measurement of electrical circuits which contain non-linear devices such as junction diodes and field effect transistors. Includes the gain and frequency response of linear amplifiers, power supplies, and other practical electronic circuits. This course is taught in a studio style with mixed lecture and lab. Pre or Corequisite: APMA 2130 and ECE 2700 AND Prerequisite: (ECE 2300 or ECE 2501 Topic Applied Circuits (link 15599)

Digital CMOS circuit design and analysis: combinational circuits, sequential circuits, and memory. Second order circuit issues. Global design issues: clocking and interconnect. Use of Cadence CAD tools. Semester long team research project investigating new areas in circuit design. Prerequisites: ECE 2630, ECE 2330.

This course introduces electrical engineering theory and its application to circuits containing active and passive circuit elements. Content includes fundamental concepts such as voltage, current, power, energy and Ohm's Law as well as circuit analysis techniques including node-voltage and mesh-current based on circuit laws and theorems such as Kirchhoff Laws, source superposition, and equivalent circuits. Prerequisite: Must have completed (APMA 1110 or MATH 1320) AND (ENGR 1624 or ENGR 1410 or ENGR 2595 Topic Engineering Foundations I or ENGR 1010)

Optoelectronics merges optics and microelectronics. Optoelectronic devices and circuits have become core technologies for several key technical areas such as telecommunications, information processing, optical storage, and sensors. This course will cover devices that generate (semiconductor light emitting diodes and lasers), modulate, amplify, switch, and detect optical signals. Also included are solar cells, photonic crystals, and plasmonics.