Complex valued nonlinear adaptive filters: noncircularity, widely linear and neural models

This book examines nonlinear adaptive filtering in the complex domain, providing theoretical information and computational principles for optimizing applications in a range of fields. It begins with a full introduction to the topic, including background theory on standard complex statistics. The authors then go on to discuss the theoretical principles of complex valued nonlinear adaptive filters, and the concept of nonlinearity in general, before presenting learning algorithms for recurrent neural networks (RNN). The authors then use this fundamental information to cover more advanced topics such as nonlinear adaptive prediction and forecasting through simulation, and a statistical framework for detecting the nature of complex random variables. The final chapter sets out potential applications using these techniques in order to illustrate the benefit of this approach.

• ISBN: 978-0-470-06635-5
• Editorial: John Wiley & Sons
• Encuadernacion: Cartoné
• Páginas: 344
• Fecha Publicación: 17/04/2009
• Nº Volúmenes: 1
• Idioma: Inglés