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Least-Mean-Square Adaptive Filters (Haykin/Least-Mean-Square Adaptive Filters) || Traveling-Wave Model of Long LMS Filters

โœ Scribed by Haykin, Simon; Widrow, Bernard


Book ID
120068572
Publisher
John Wiley & Sons, Inc.
Year
2005
Weight
340 KB
Category
Article
ISBN
0471215708

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๐Ÿ“œ SIMILAR VOLUMES


Least-Mean-Square Adaptive Filters (Hayk
โœ Haykin, Simon; Widrow, Bernard ๐Ÿ“‚ Article ๐Ÿ“… 2005 ๐Ÿ› John Wiley & Sons, Inc. ๐ŸŒ English โš– 112 KB

The least-mean-square (LMS) algorithm represents the cornerstone for the design of adaptive transversal filters. Haykin (director, Adaptive Systems Laboratory, McMaster University), and Widrow (adaptive systems, Stanford University), one of the original inventors of the algorithm, look at properties

Robust least mean square adaptive FIR fi
โœ Banjac, Z.; Kovacevic, B.; Veinovic, M.; Milosavljevic, M. ๐Ÿ“‚ Article ๐Ÿ“… 2001 ๐Ÿ› The Institution of Electrical Engineers ๐ŸŒ English โš– 504 KB
Kernel Adaptive Filtering || Kernel Leas
โœ Liu, Weifeng; Prncipe, Jos C.; Haykin, Simon ๐Ÿ“‚ Article ๐Ÿ“… 2010 ๐Ÿ› John Wiley & Sons, Inc. ๐ŸŒ English โš– 723 KB

**Online learning from a signal processing perspective** There is increased interest in kernel learning algorithms in neural networks and a growing need for nonlinear adaptive algorithms in advanced signal processing, communications, and controls. *Kernel Adaptive Filtering* is the first book to pr