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Proportionate-Type Normalized Least Mean Square Algorithms
Kevin Wagner
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Description for Proportionate-Type Normalized Least Mean Square Algorithms
Hardback. Proportionate-type normalized least mean square (PtNLMS) offer low computational complexity and fast convergence times, for sparse impulse responses in network and acoustic echo cancellation applications. Introducing this important subject, this book then develops and analyzes these algorithms. Num Pages: 192 pages, Illustrations. BIC Classification: TJ. Category: (P) Professional & Vocational. Dimension: 240 x 158 x 21. Weight in Grams: 444.
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.
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Format
Hardback
Publication date
2013
Publisher
ISTE Ltd and John Wiley & Sons Inc United Kingdom
Number of pages
192
Condition
New
Number of Pages
192
Place of Publication
London, United Kingdom
ISBN
9781848214705
SKU
V9781848214705
Shipping Time
Usually ships in 7 to 11 working days
Ref
99-1
About Kevin Wagner
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. Miloš Doroslovacki has been with the Department of Electrical and Computer Engineering at George Washington University, USA since 1995, where he is now an ... Read more
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