This book presents the first comprehensive treatment of neural networks from an engineering perspective. Thorough, well-organized, and completely up-to-date, it examines all the important aspects of this emerging technology.

Neural Networks: A Comprehensive Foundation

Computers & Technology

SIMON HAYKIN

Certification

Macmillan Coll Div

Modern Filters

Engineering & Transportation

Engineering

Prentice Hall International Paperback Editions

This book develops the mathematical theory of linear adaptive filters with finite impulse response. Examples and computer experiment applications illustrate the theory and principles. The second edition has also been restructured with an introduction followed by four parts: discrete-time wide-sense station stochastic process; linear optimum filtering; linear FIR adaptive filtering; limitations, extensions and discussions. New features includes new chapters on QR decomposition-based lattice filters, on blind deconvolution, new appendix material on complex variables and regulation.

Adaptive Filter Theory (Prentice-Hall Information and System Sciences Series)

PRENTICE/HALL

This best-selling, easy to read book offers the most complete discussion on the theories and principles behind today's most advanced communications systems. Throughout, Haykin emphasizes the statistical underpinnings of communication theory in a complete and detailed manner. Readers are guided though topics ranging from pulse modulation and passband digital transmission to random processes and error-control coding. The fifth edition has also been revised to include an extensive treatment of digital communications.

Communication Systems 5/E

Michael Moher

John Wiley&Sons

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 present a comprehensive, unifying introduction to online learning algorithms in reproducing kernel Hilbert spaces. Based on research being conducted in the Computational Neuro-Engineering Laboratory at the University of Florida and in the Cognitive Systems Laboratory at McMaster University, Ontario, Canada, this unique resource elevates the adaptive filtering theory to a new level, presenting a new design methodology of nonlinear adaptive filters. <ul>
<li> Covers the kernel least mean squares algorithm, kernel affine projection algorithms, the kernel recursive least squares algorithm, the theory of Gaussian process regression, and the extended kernel recursive least squares algorithm </li> <li> Presents a powerful model-selection method called maximum marginal likelihood </li> <li> Addresses the principal bottleneck of kernel adaptive filters―their growing structure </li> <li> Features twelve computer-oriented experiments to reinforce the concepts, with MATLAB codes downloadable from the authors' Web site </li> <li> Concludes each chapter with a summary of the state of the art and potential future directions for original research </li> </ul>
Kernel Adaptive Filtering is ideal for engineers, computer scientists, and graduate students interested in nonlinear adaptive systems for online applications (applications where the data stream arrives one sample at a time and incremental optimal solutions are desirable). It is also a useful guide for those who look for nonlinear adaptive filtering methodologies to solve practical problems.

Kernel Adaptive Filtering: A Comprehensive Introduction

Weifeng Liu

José C. Principe

Computer Science

wiley

Offers the most complete, up-to-date coverage available on the principles of digital communications. Focuses on basic issues, relating theory to practice wherever possible. Numerous examples, worked out in detail, have been included to help the reader develop an intuitive grasp of the theory. Topics covered include the sampling process, digital modulation techniques, error-control coding, robust quantization for pulse-code modulation, coding speech at low bit radio, information theoretic concepts, coding and computer communication. Because the book covers a broad range of topics in digital communications, it should satisfy a variety of backgrounds and interests, and offers a great deal of flexibility for teaching the course. The author has included suggested course outlines for courses at the undergraduate or graduate levels.

Digital Communications

John Wiley&Sons, Inc.

Fundamentals of Cognitive Radio (Adaptive and Cognitive Dynamic Systems: Signal Processing, Learning, Communications and Control)

Cognitive Dynamic Systems

Cambridge University Press

Radar Array Processing presents modern techniques and methods for processingradar signals received by an array of antenna elements. With the recent rapid growth of the technology of hardware for digital signal processing, itis now possible to apply this to radar signals and thus to enlist the full power of sophisticated computational algorithms. Topics covered in detail here include: super-resolution methods of array signal processing as applied to radar, adaptive beam forming for radar, and radar imaging. This book will be of interest to researchers and studentsin the radar community and also in related fields such as sonar, seismology, acoustics and radio astronomy.

Radar Array Processing (Springer Series in Information Sciences)

Springer

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Books by SIMON HAYKIN