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

"For those involved in the design and implementation of signal processing algorithms, this book strikes a balance between highly theoretical expositions and the

Nonlinear Signal Processing: A Statistical Approach focuses on unifying the study of a broad and important class of nonlinear signal processing algorithms which

Complex-valued random signals are embedded in the very fabric of science and engineering, yet the usual assumptions made about their statistical behavior are of

We consider robust covariance estimation with an emphasis on Tyler's M-estimator. This method provides accurate inference of an unknown covariance in non-standa