SIMON HAYKIN

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Kalman filtering is a well-established topic in the field of control and signal processing and represents by far the most refined method for the design of neural networks. This book takes a non-traditional non-linear approach and reflects the fact that most practical applications are non-linear.

Die erschöpfendste Behandlung der digitalen Kommunikationstechnik in einem Lehrbuch für Studenten der unteren Semester! Der bewährte Bestseller wurde für diese Neuauflage umfassend überarbeitet und auf den neuesten Stand gebracht. Ausführlich und gut verständlich werden die statistischen Grundlagen der Kommunikationstheorie erläutert. Auch moder...

Design and MATLAB concepts have been integrated in text. * Integrates applications as it relates

"IEEE Press is proud to present the first selected reprint volume devoted to the new field of...

Online learning from a signal processing perspectiveThere 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 present a comprehensive, unifying introduction to online ...

The second edition of this accessible book provides readers with an introductory treatment of communication theory as applied to the transmission of information-bearing signals. While it covers analog communications, the emphasis is placed on digital technology. It begins by presenting the functional blocks that constitute the transmitter and re...