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Complex Valued Nonlinear Adaptive Filters
Danilo P. Mandic
€ 147.70
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Description for Complex Valued Nonlinear Adaptive Filters
Hardcover. The filtering of real world signals requires an adaptive mode of operation to deal with the statistically nonstationary nature of the data. Feedback and nonlinearity within filtering architectures are needed to cater for long time dependencies and possibly nonlinear signal generating mechanisms. Series: Adaptive and Learning Systems for Signal Processing, Communications and Control. Num Pages: 344 pages, Illustrations. BIC Classification: TJK; UYS. Category: (P) Professional & Vocational. Dimension: 256 x 175 x 24. Weight in Grams: 754.
This book was written in response to the growing demand for a text that provides a unified treatment of linear and nonlinear complex valued adaptive filters, and methods for the processing of general complex signals (circular and noncircular). It brings together adaptive filtering algorithms for feedforward (transversal) and feedback architectures and the recent developments in the statistics of complex variable, under the powerful frameworks of CR (Wirtinger) calculus and augmented complex statistics. This offers a number of theoretical performance gains, which is illustrated on both stochastic gradient algorithms, such as the augmented complex least mean square (ACLMS), and those based ... Read more
This book was written in response to the growing demand for a text that provides a unified treatment of linear and nonlinear complex valued adaptive filters, and methods for the processing of general complex signals (circular and noncircular). It brings together adaptive filtering algorithms for feedforward (transversal) and feedback architectures and the recent developments in the statistics of complex variable, under the powerful frameworks of CR (Wirtinger) calculus and augmented complex statistics. This offers a number of theoretical performance gains, which is illustrated on both stochastic gradient algorithms, such as the augmented complex least mean square (ACLMS), and those based ... Read more
Product Details
Publisher
John Wiley and Sons Ltd United Kingdom
Number of pages
344
Format
Hardback
Publication date
2009
Series
Adaptive and Learning Systems for Signal Processing, Communications and Control
Condition
New
Number of Pages
344
Place of Publication
New York, United States
ISBN
9780470066355
SKU
V9780470066355
Shipping Time
Usually ships in 15 to 20 working days
Ref
99-15
About Danilo P. Mandic
Danilo Mandic, Department of Electrical and Electronic Engineering, Imperial College London, London Dr Mandic is currently a Reader in Signal Processing at Imperial College, London. He is an experienced author, having written the book Recurrent Neural Networks for Prediction: Learning Algorithms, Architectures and Stability (Wiley, 2001), and more than 150 published journal and conference papers on signal and image processing. ... Read more
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