Presents a systematic framework for system identification and information processing, investigating system identification from an information theory point of view. This book is divided into six chapters, which cover the information needed to understand the theory and application of system parameter [...]

This book presents the first cohesive treatment of Information Theoretic Learning (ITL) algorithms to adapt linear or nonlinear learning machines both in supervised or unsupervised paradigms. ITL is a framework where the conventional concepts of second order statistics (covariance, L2 distances, cor[...]