400

EE 401 Electrical Power and Renewable Energy Systems

This course explores the principles and technologies behind electrical power generation, transmission, distribution, storage, and the integration of renewable energy sources into the electrical grid. Students will gain a comprehensive understanding of conventional and renewable energy systems, grid integration challenges, and sustainable energy practices. Students will explore current topics such as preventing cyber-attacks.

3

Credits

3

EE 403 Communication Systems

Introduction to analog and digital communication systems with emphasis on modulation, demodulation, encoding, decoding, and synchronization techniques used in wireless systems. Python is used to simulate communication systems and to write a software defined receiver (SDR) for a real RF signal.

3

Prerequisites

EE 262

Credits

3

EE 410 Engineering Applications of Artificial Intelligence

How will smart transportation learn traffic patterns and road conditions? How will smart buildings learn to keep their occupants comfortable? How do we use predictive models for future design decisions? Students in this course will use Python and real-world problems to learn about engineering applications of artificial intelligence and machine learning.

3

Prerequisites

Prior Programming Experience

Cross Listed Courses

EGR 410

Credits

3

EE 435 Verilog Digital Systems Modeling

Introduction to Verilog-based design process. Hierarchical modeling methodology. Basic Verilog language structures for modeling digital hardware functions. Modules and ports. Gate-level modeling. Data flow modeling. Behavioral modeling. Tasks and functions. Useful modeling techniques in digital system design. Component timing and delay modeling. Logic synthesis with Verilog HDL.

3

Prerequisites

EE 332

Credits

3

EE 463 Digital Signal Processing

This course covers techniques used to process digital signals in applications such as audio filtering and speech recognition. Topics include analog-to-digital and digital-to-analog conversions, aliasing, quantization, discrete-time signals and systems, discrete-time Fourier transform, Z-transform, and digital filter design. MATLAB is used to demonstrate concepts and to process real signals.
3

Prerequisites

EE 262

Credits

3

EE 464 Real-time Digital Signal Processing

Introduction to the hardware and software used in real-time digital signal processing (DSP) systems. Topics include analog-to-digital and digital-to-analog converters, DSP chip architecture, and special software techniques such as frame-based processing, circular buffering, digital filters, and the Fast Fourier Transform. Students will implement real-time DSP systems using C language and will run them on a DSP board.

3

Prerequisites

EE 262

Credits

3

EE 465 Introduction to Neuroimaging and Brain Stimulation

Applications of electrical engineering in recording and modifying neural activity of the brain. Topics include basics of brain imaging techniques such as electroencephalography (EEG), magnetic resonance imaging (MRI), and functional magnetic resonance imaging (fMRI). Introduction to treatment methods utilizing electric and magnetic fields to alter brain activity such as repetitive transcranial magnetic stimulation (rTMS).

3

Prerequisites

EE 262

Credits

3

EE 490 Directed Study

Selected study or project in electrical engineering for upper-division students. Must be arranged between the student and an individual faculty member and subsequently approved by the dean of engineering. No more than three hours of directed study taken at the University may be used for elective credits to satisfy degree requirements.

Variable

Credits

Variable

EE 491 One Time Course Offering

Credit Arranged.

1 to 12

Credits

1 to 12

EE 493 Research

Faculty-directed student research. Before enrolling, a student must consult with a faculty member to define the project. May be repeated for credit. Course is graded A-F.
1 to 3

Prerequisites

Upper division standing.

Credits

1 to 3