ECE257: Signal 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. Enrollment is restricted to graduate students.

5 credits

Year	Fall	Winter	Spring	Summer
2025-26		Section 01 Hao Ye (hye30)

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