ECE 257Signal Processing with Machine Learning
Explores the intersection of classical signal processing and modern machine learning. Covers stochastic signal processing, adaptive filtering (Wiener, LMS), and time-series analysis. Bridges these topics to machine learning fundamentals, including neural networks, sparse representations (Lasso, compressed sensing), and deep learning models (RNNs, LSTMs) for sequential data.
Prerequisite(s): Enrollment is restricted to graduate students.
Find a section and add it to your scheduleLive seat counts, time-conflict checks and the walk from your previous class.
When it runs
Winter 2026Open Winter 2026
| Section | Type | When | Where | Instructor | Seats |
|---|---|---|---|---|---|
| 01 | Lecture | Tue Thu 5:20pm–6:55pm | Thimann Lab 101 | H. Ye | Open 6/15 |
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