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.

Course Details

  • Grading Basis: Letter Grade or Credit/No Credit

Prerequisites

EE 178; linear systems and Fourier transforms at the level of EE 102A, 102B, or 261

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