ECE 603

Statistical Signal Processing

Graduate

Fall 2023 · Statistical Digital Signal Processing

Readings

Statistical Digital Signal Processing and Modeling
required
Adaptive Filter Theory by Simon Haykin. An Introduction to Statistical Signal Processing by Robert M. Gray and Lee Davisson (available online: https://ee.stanford.edu/∼gray/sp.pdf).
unspecified

Fall 2021 · Statistical Digital Signal Processing

Statistical Digital Signal Processing and Modeling by Monsoon H. Hayes
required
Adaptive Filter Theory by Simon Haykin. An Introduction to Statistical Signal Processing by Robert M. Gray and Lee Davisson (available online: https://ee.stanford.edu/∼gray/sp.pdf).
unspecified

Winter 2020

Review of Probability: Expectations, Conditioning, the Gaussian distribution, CLT, and SLLN.
Introduction to point estimation theory. Minimum mean square estimates.
Consistency, efficiency of estimators. Fisher information matrix and the Cramer-Rao lower bound. Sufficient statistics and the Rao-Blackwell theorem
Resursive estimators, maximum likelihood estimators- The EM algorithm
Introduction to hypothesis testing. Bayesian decision theory, The Neyman-Pearson lemma. Kullback-Liebler information. Wasserstein metric. 1
Filtering, prediction and smoothing of w.s.s. sequences. Recursive least squares. Yule-Walker equations.
Gauss-Markov processes and state space models. Discrete-time Kalman filtering. Asymptotic theory.
Mathematical tools for learning. Convergence and ode method. Stochastic gradient. Robbins- Monroe and Kiefer-Wolfowitz algorithms. Frank-Wolf.

B. Picinbono, Random Signals and Systems , Prentice-Hall, 1993
unspecified
T. Kailath, A. Sayed, and B. Hassibi; Linear Estimation, Prentice-Hall, 1999.
unspecified
V. Poor; Introduction to signal detection and estimation, Springer-Verlag
unspecified
A. V. Balakrishnan, Kalman filtering theory, Optimization Software Publ, 1995
unspecified

Spring 2020 · Statistical Digital Signal Processing

Statistical Digital Signal Processing and Modeling by Monsoon H. Hayes
required
Adaptive Filter Theory by Simon Haykin. An Introduction to Statistical Signal Processing by Robert M. Gray and Lee Davisson (available online: https://ee.stanford.edu/∼gray/sp.pdf).
unspecified

Spring 2017

Sources

Course catalogue ↗2026–2027
course_outline ↗Fall 2023
course_outline ↗Fall 2021
course_outline ↗Winter 2020
course_outline ↗Spring 2020
course_outline ↗Spring 2017
Official public PDF outline or course description. Materials and topic extracts may be partial; consult the linked source for the full list.
Official public PDF outline or course description. Materials and topic extracts may be partial; consult the linked source for the full list.
Official public PDF outline or course description. Materials and topic extracts may be partial; consult the linked source for the full list.
Official public PDF outline or course description. Materials and topic extracts may be partial; consult the linked source for the full list.
Public departmental course outline. Source may be archival; no current-term assignment is implied. Bibliographic details are preserved in textbook notes.