Proportionate-Type Normalized Least Mean Square Algorithms Contributor(s): Wagner, Kevin (Author), Doroslovacki, Milos (Author) |
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ISBN: 1848214707 ISBN-13: 9781848214705 Publisher: Wiley-Iste
Binding Type: Hardcover - See All Available Formats & Editions Published: July 2013 |
Additional Information |
BISAC Categories: - Computers | Programming - Algorithms |
Dewey: 518.1 |
LCCN: 2013937864 |
Physical Information: 0.8" H x 6.2" W x 9.3" L (1.05 lbs) 192 pages |
Features: Bibliography, Illustrated, Index |
Descriptions, Reviews, Etc. |
Publisher Description: The topic of this book is proportionate-type normalized least mean squares (PtNLMS) adaptive filtering algorithms, which attempt to estimate an unknown impulse response by adaptively giving gains proportionate to an estimate of the impulse response and the current measured error. These algorithms offer low computational complexity and fast convergence times for sparse impulse responses in network and acoustic echo cancellation applications. New PtNLMS algorithms are developed by choosing gains that optimize user-defined criteria, such as mean square error, at all times. PtNLMS algorithms are extended from real-valued signals to complex-valued signals. The computational complexity of the presented algorithms is examined. Contents 1. Introduction to PtNLMS Algorithms About the Authors Kevin Wagner has been a physicist with the Radar Division of the Naval Research Laboratory, Washington, DC, USA since 2001. His research interests are in the area of adaptive signal processing and non-convex optimization. |
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