ENEE634

Learning and Statistical Signal Processing

Prerequisite: ENEE620 and ENEE630. Adaptive learning and statistical signal processing, including: numerical analysis; principal component analysis and support vector machines; adaptive signal processing (supervised learning); blind equalization and identification (unsupervised learning); antenna array and MIMO signal processing; space-time and space-time-frequency coding; neural networks (nonlinear adaptive learning); advanced topics on machine learning, such as online and deep learning.

Fall 2025

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Past Semesters

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During the Spring 2020 and Spring 2021 semesters, students could choose to take some of their courses pass-fail mid-semester which skews grade data aggregated across multiple semesters.

Average GPA of 3.45 between 45 students*

ENEE634 Grade Distribution+-0510152025303540455055606570% of studentsABCDFWother
A-: 8.89%
A: 42.22%
A+: 15.56%
B-: 2.22%
B: 11.11%
B+: 2.22%
C: 4.44%
D: 2.22%
W: 4.44%
other: 6.67%
* "W"s are considered to be 0.0 quality points. "Other" grades are not factored into GPA calculation. Grade data not guaranteed to be correct.