Blind Source Separation of Convolutive Mixtures of Speech
This chapter introduces the blind source separation (BSS) of convolutive mixtures of acoustic signals, especially speech. A statistical and computational technique, called independent component analysis (ICA), is examined. By achieving nonlinear decorrela
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Springer-Verlag Berlin Heidelberg GmbH
Jacob Benesty · Yiteng Huang (Eds)
Adaptive Signal Processing Applications to Real-World Problems With 122 Figures
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Jacob Benesty Yiteng Huang Bell Labs Lucent Technologies 700 Mountain Avenue 07974-0636 Murray Hill, NJ USA
Library of Congress Cataloging-in-Publication Data Benesty, Jacob. Adaptive signal processing: applications to real-world problems / Jacob Benesty, Yiteng Huang. p.cm. Includes bibliographical references. ISBN 978-3-642-05507-2 ISBN 978-3-662-11028-7 (eBook) DOI 10.1007/978-3-662-11028-7 1. Adaptive signal processing. I. Huang, Yiteng. II. Title TK 5102.9.B4515 2003 621.382’2--dc21 2002036471
ISBN 978-3-642-05507-2 This work is subject to copyright. All rights are reserved, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilm or in other ways, and storage in data banks. Duplication of this publication or parts thereof is permitted only under the provisions of the German Copyright Law of September 9, 1965, in its current version, and permission for use must always be obtained from Springer-Verlag Berlin Heidelberg GmbH. Violations are liable for prosecution act under German Copyright Law.
http://www.springer.de © Springer-Verlag Berlin Heidelberg 2003 Originally published by Springer-Verlag Berlin Heidelberg New York in 2003 Softcover reprint of the hardcover 1st edition 2003 The use of general descriptive names, registered names, trademarks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. Typesetting: Digital data supplied by editors Cover-Design: design & production GmbH, Heidelberg Printed on acid-free paper 62/3020 Rw 5 4 3 2 1 0
Preface
By adaptive signal processing, we mean, in general, adaptive filtering. In unknown environments where we need to model, identify, or track time-varying channels, adaptive filtering has been proven to be an effective and powerful tool. As a result, this tool is now in use in many different fields. Since the invention, by Widrow and Hoff in 1959, of one of the first adaptive filters, the so-called least-mean-square, many applications appeared to have the potential to use this fundamental concept. While the number of applications (using adaptive algorithms) has been (and keeps) flourishing with time, thanks to several successes, the need for more sophisticated adaptive algorithms became obvious as real-world problems are more complex and more demanding. Even though the theory of adaptive filtering is already a well-established topic in signal processing, new and improved concepts are discovered every year by researchers. Some of these recent approaches are discussed in this book. The goal of this book is to provide, for the first time, a reference to the hottest real-world applications where adaptive filtering techniques play an important role.
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