Topics In Robust Statistical Signal Processing

Topics in Robust Statistical Signal Processing

This dissertation addresses several problems in robust signal processing. The term robust in this context implies insensitivity to small deviations from the assumed statistical description of the signal and/or noise. The first part of this thesis considers the problem of linear minimum-mean-square-error estimation of a stationary signal observed in additive stationary noise when knowledge of the signal spectrum and noise spectrum is inexact. In the second part of this dissertation, a previously developed cohesive theory of robust hypothesis testing in which uncertainty is modeled via 2-alternating Choquet capacity classes is considered in light of recent applications of this theory to problems in robust signal processing and communication theory.

Robust Statistics for Signal Processing

Understand the benefits of robust statistics for signal processing using this unique and authoritative text.

Statistical Signal Processing