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 2300, and ECE 2200 or equivalent.

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))

Explores the statistical methods of analyzing communications systems: random signals and noise, statistical communication theory, and digital communications. Analysis of baseband and carrier transmission techniques; and design examples in satellite communications. Prerequisite: (APMA 3100 or MATH 3100) AND (ECE 3750 or ECE 2700)

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.

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

An introduction to digital signal processing. Topics include discrete-time signals and systems, application of z-transforms, the discrete-time Fourier transform, sampling, digital filter design, the discrete Fourier transform, the fast Fourier transform, quantization effects and nonlinear filters. Prerequisite: 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

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.

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.