Synopses & Reviews
A complete, one-stop reference on the state of the art of unsupervised adaptive filtering
While unsupervised adaptive filtering has its roots in the 1960s, more recent advances in signal processing, information theory, imaging, and remote sensing have made this a hot area for research in several diverse fields. This book brings together cutting-edge information previously available only in disparate papers and articles, presenting a thorough and integrated treatment of the two major classes of algorithms used in the field, namely, blind signal separation and blind channel equalization algorithms.
Divided into two volumes for ease of presentation, this important work shows how these algorithms, although developed independently, are closely related foundations of unsupervised adaptive filtering. Through contributions by the foremost experts on the subject, the book provides an up-to-date account of research findings, explains the underlying theory, and discusses potential applications in diverse fields. More than 100 illustrations as well as case studies, appendices, and references further enhance this excellent resource. Following coverage begun in Volume I: Blind Source Separation, this volume discusses:
* The core of FSE-CMA behavior theory
* Relationships between blind deconvolution and blind source separation
* Blind separation of independent sources based on multiuser kurtosis optimization criteria
Synopsis
Un berwachte adaptive Filterung bedeutet, da das System automatisch auf Ver nderungen der Bedingungen reagiert: Die Filter k nnen sich verschiedenen Situationen anpassen, ohne da ein Mensch eingreifen m te. Hunderte von Beitr gen zu diesem u erst aktuellen Forschungsfeld sind in der Fachpresse erschienen. Dieser Band fa t den derzeitigen Erkenntnisstand zusammen und erspart Ihnen damit eine zeitraubende Recherche. (04/00)
Synopsis
Unsupervised adaptive filters let systems respond and adapt automatically to changing conditions without the need for human supervision. With applications to signal processing, information theory, imaging, and remote sensing, among others, this is an area of intense research. This book describes the current state of the art in the field.
Synopsis
* Blind separation of independent sources based on multiuser kurtosis optimization criteria
Table of Contents
Introduction (S. Haykin).
The Core of FSE-CMA Behavior Theory (C. Johnson, et al.).
Relationships between Blind Deconvolution and Blind Source Separation (S. Douglas & S. Haykin).
Blind Separation of Independent Sources Based on Multiuser Kurtosis Optimization Criteria (C. Papadias).
Index.