ORIE 5586

Statistical Signal Processing and Reinforcement Learning

Course Description

Course information provided by the Courses of Study 2018-2019.

Core ECE course covering basics of signal processing and data analysis. The first half of the course covers fundamentals of signals and systems, including the discrete Fourier transform, transfer functions, frequency selective filtering, adaptive filtering, linear prediction, and applications in noise cancellation and communication systems. The second half covers the basics of probabilistic models, stochastic simulation, Markov processes and Bayesian inference. Finally, topics in high dimensional signal processing including model selection, sparse signal processing and principal component analysis are covered. Throughout the course, applications in communication systems, sensing systems and machine learning will be emphasized.

• Students will learn state of the art methods in modern statistical signal processing backed up with applications in communication and sensing systems.

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