An applied physics course in electricity and magnetism, with emphasis on the technologies derived from them. An integrated lab component will provide team-based, hands-on examples and reviews of key concepts. Calculus 3 (Multivariable) may be taken concurrently; however, students should be proficient with vectors and calculus, including the chain rule and trigonometric functions. Prerequisite: PHYS 1425 or PHYS 1420, and APMA 1110

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)

Introduction to analysis and design of digital systems from switches to gates to components to CPU. Analysis and design of combinational and sequential components including multiplexers and demultiplexers, decoders and encoders, comparators, adders and ALU, registers and register files, counters and timers, RTL design, culminating in the design of a simple programmable processor. 10-12 studio design activities. Cross-listed as CS 2330.

Learn about and experiment with machine learning algorithms using Python. Applications include image classification, removing noise from images, and linear regression. Students will collect and interpret data, learn machine learning theory, build systems-level thinking skills required to strategize how to break the problem down into various functions, and to implement, test and document those functions. Prerequisite: CS 111X

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)

Develops tools for analyzing signals and systems in continuous and discrete-time, for controls, communications, signal processing and machine learning. Primary concepts are the representation of signals and linear systems in the time domain (convolution, differential equations, state-space representation) and in the frequency domain (Fourier/Laplace analysis) including practical programming examples. Pre or Coreq: APMA 2130 AND Prerequisite (ECE 2300 or ECE 2501 Topic Applied Circuits (link 15599))

Analyzes the basics of band theory and atomic structure; charge-transport in solids; current voltage characteristics of semiconductor devices, including p-n junction diodes, bipolar transistors, Schottky diodes, and insulated-gate field-effect transistors; electron emission; and superconductive devices. Prerequisite: ECE 2630.

Analyzes the basic laws of electromagnetic theory, beginning with static electric and magnetic fields, and concluding with dynamic E&M fields; plane wave propagation in various media; Maxwell's Laws in differential and integral form; electrical properties of matter; transmission lines, waveguides, and elementary antennas. Prerequisite: APMA 2130 & ECE 2630

An embedded computer is designed to efficiently interact directly with its physical environment. This lab-based course explores architecture and interface issues relating to the design, evaluation and implementation of embedded systems . Topics include hardware and software organization, power management, digital and analog I/O devices, memory systems, timing and interrupts.Prerequisites: (ECE 2300 or ECE 2630) AND ECE 2330 AND CS 2130

Construction of electronic circuit design to specifications. Focuses on computer simulation, construction, and testing of designed circuits in the laboratory to verify predicted performance. Includes differential amplifiers, feedback amplifiers, multivibrators, and digital circuits. Three lecture and three laboratory hours. Prerequisite: ECE 2600 or ECE 2660

Design and analysis of wireless communication circuits. Topics covered include transmission lines, antennas, filters, amplifiers, mixers, noise, and modulation techniques. The course is built around a semester long design project. Prerequisite ECE 2700 or ECE 3750

Focuses on the techniques for designing and analyzing dependable computer-based systems. Topics include fault models and effects, fault avoidance techniques, hardware redundancy, error detecting and correcting codes, time redundancy, software redundancy, combinatorial reliability modeling, Markov reliability modeling, availability modeling, maintainability, safety modeling, trade-off analysis, design for testability, and the testing of redundant digital systems. Cross-listed as CS 4434. Prerequisite: ECE 3430 or CS 3330 and APMA 3100 or APMA 3110.

Design, analysis and testing of an embedded computer system to meet specific needs, considering public health, safety and welfare as well as societal impacts. Tradeoff analysis and constraint satisfaction facilitated by the use of appropriate engineering analysis techniques. Semester-long team project develops physical prototype. Counts as major design experience for ECE students. Prerequisites (ECE 3430 or ECE 3502 ECR II) AND (ECE 3750 or ECE 2700) AND 4th year standing

A fourth-level undergraduate course covering a topic not normally covered in the course offerings. The topic usually reflects new developments in the electrical and computer engineering field. Offering is based on student and faculty interests.

A fourth-level undergraduate course covering a topic not normally covered in the course offerings. The topic usually reflects new developments in the electrical and computer engineering field. Offering is based on student and faculty interests.

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.

Design, analysis and testing of an electrical system to meet specific needs, considering applicable standards, health, safety, welfare, and societal impacts as well as tradeoff and constraint considerations. Semester-long team project develops physical prototype (not simulation). Counts major design experience for students in ECE. Prerequisites (ECE 3430 or ECE 3502 ECR II) AND (ECE 3750 or ECE 2700) AND 4th year standing

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.

Introduces semiconductor device operation based on energy bands and carrier statistics. Describes operation of p-n junctions and metal-semiconductor junctions. Extends this knowledge to descriptions of bipolar and field effect transistors, and other microelectronic devices. Related courses: ECE 5150, 6155, and 6167. Prerequisite: ECE 3103 or equivalent, or solid state materials/physics course.

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.

A first-level graduate course covering a topic not normally covered in the graduate course offerings. The topic will usually reflect new developments in the electrical and computer engineering field. Offering is based on student and faculty interests. Prerequisite: Instructor permission.

A first-level graduate course covering a topic not normally covered in the graduate course offerings. The topic will usually reflect new developments in the electrical and computer engineering field. Offering is based on student and faculty interests. Prerequisite:  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.  It is a one-credit course required for all first-year ECE graduate students. 

Topics include probability spaces; random variables and vectors; and random sequences and processes; especially specification and classification. Includes detailed discussion of second-order stationary processes and Markov processes; inequalities, convergence, laws of large numbers, central limit theorem, ergodic, theorems; and MS estimation, Linear MS estimation, and the Orthogonality Principle. Prerequisite: APMA 3100, MATH 3100, or equivalent.

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.

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.

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.

Formal record of student commitment to master's thesis research under the guidance of a faculty advisor. May be repeated as necessary.

For doctoral students.

Formal record of student commitment to doctoral research under the guidance of a faculty advisor. May be repeated as necessary.