Unsupervised adaptive filtering is an area of intense research. Applications are found in signal processing, information theory, imaging, and remote sensing among others. This title presents the foremost researchers in this area providing a single source of reference for this field.
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A complete, one–stop reference on the state of the act 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. Topics in Volume I include:
"Contributions are by fore–most experts, and provides up–to–date research findings." (IEE Signal Processing Magazine, Vol. 18, No. 1, January 2001)
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