Introduction to Statistical Signal Processing

Course Description

Review of basic probability and random variables. Random vectors and processes; convergence and limit theorems; IID, independent increment, Markov, and Gaussian random processes; stationary random processes; autocorrelation and power spectral density; mean square error estimation, detection, and linear estimation. Formerly EE 278B.

Prerequisites

EE178 and linear systems and Fourier transforms at the level of EE102A,B or EE261.

Syllabus Link

None available.
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