Complex Valued Nonlinear Adaptive Filters: Noncircularity, Widely Linear and Neural Models

Complex Valued Nonlinear Adaptive Filters: Noncircularity, Widely Linear and Neural Models

Author(s): Danilo P. Mandic, Vanessa Su Lee Goh

Published Online: 16 APR 2009

Print ISBN: 9780470066355

Online ISBN: 9780470742624

DOI: 10.1002/9780470742624

About this Book

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 on Kalman filters. This work is supported by a number of simulations using synthetic and real world data, including the noncircular and intermittent radar and wind signals.

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