Offered in 2020 Spring, 2021 Spring, 2022 Spring, 2023 Fall, 2024 Spring, 2025 Spring, 2025 Fall
An introduction to continuous and discrete signal and system models and analyses. Topics include discrete and continuous convolution, Fourier series and transforms, Laplace transforms, and Z-transforms with application examples, including amplitude modulation and sampling theorem.
Prerequisite: Engineering standing, MA 214 and a C or better in EE 221.
Offered in 2019 Fall, 2021 Fall, 2022 Fall, 2023 Fall, 2024 Fall, 2025 Fall
Lectures and laboratory exercises on signal and systems modeling. Topics include noise models and analysis, filter design, modulation techniques, sampling, discrete Fourier transforms, state variable models, and feedback design with an emphasis on using computer software for analysis and simulation.
Prerequisite: EE 421G and MA 320.
Offered in 2024 Fall
A detailed investigation of a topic of current significance and interest in electrical engineering. An introduction to brain machine interfaces. Topics include signal processing and classification techniques for electroencephalograms (EEG) based brain computer interfaces.
Prerequisite: EE 421G.
Offered in 2020 Fall
A detailed investigation of a topic of current significance and interest in electrical engineering. An introduction to neural models and signals and their analyses. Topics include computational models for single and multi-neurons, spike sorting, signal processing and classification methods for neural signals, electroencephalograms (EEG) source imaging, and brain computer interfaces.
Prerequisite: EE 421G.