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.

For graduate-level neural network courses offered in the departments of Computer Engineering, Electrical Engineering, and Computer Science. Renowned for its thoroughness and readability, this well-organized and completely up-to-date text remains the most comprehensive treatment of neural networks from an engineering perspective. Matlab codes used for the computer experiments in the text are available for download at: http: //www.pearsonhighered.com/haykin/ Refocused, revised and renamed to reflect the duality of neural networks and learning machines, this edition recognizes that the subject matter is richer when these topics are studied together. Ideas drawn from neural networks and machine learning are hybridized to perform improved learning tasks beyond the capability of either independently.

This book provides a rigorous treatment of deterministic and random signals. It offers detailed information on topics including random signals, system modelling and system analysis. System analysis in frequency domain using Fourier transform and Laplace transform is explained with theory and numerical problems. The advanced techniques used for signal processing, especially for speech and image processing, are discussed. The properties of continuous time and discrete time signals are explained with a number of numerical problems. The physical significance of different properties is explained using real-life examples. To aid understanding, concept check questions, review questions, a summary of important concepts, and frequently asked questions are included. MATLAB programs, with output plots and simulation examples, are provided for each concept. Students can execute these simulations and verify the outputs.

A handbook on recent advancements and the state of the art in array processing and sensor Networks Handbook on Array Processing and Sensor Networks provides readers with a collection of tutorial articles contributed by world-renowned experts on recent advancements and the state of the art in array processing and sensor networks. Focusing on fundamental principles as well as applications, the handbook provides exhaustive coverage of: wavelets; spatial spectrum estimation; MIMO radio propagation; robustness issues in sensor array processing; wireless communications and sensing in multi-path environments using multi-antenna transceivers; implicit training and array processing for digital communications systems; unitary design of radar waveform diversity sets; acoustic array processing for speech enhancement; acoustic beamforming for hearing aid applications; undetermined blind source separation using acoustic arrays; array processing in astronomy; digital 3D/4D ultrasound imaging technology; self-localization of sensor networks; multi-target tracking and classification in collaborative sensor networks via sequential Monte Carlo; energy-efficient decentralized estimation; sensor data fusion with application to multi-target tracking; distributed algorithms in sensor networks; cooperative communications; distributed source coding; network coding for sensor networks; information-theoretic studies of wireless networks; distributed adaptive learning mechanisms; routing for statistical inference in sensor networks; spectrum estimation in cognitive radios; nonparametric techniques for pedestrian tracking in wireless local area networks; signal processing and networking via the theory of global games; biochemical transport modeling, estimation, and detection in realistic environments; and security and privacy for sensor networks. Handbook on Array Processing and Sensor Networks is the first book of its kind and will appeal to researchers, professors, and graduate students in array processing, sensor networks, advanced signal processing, and networking.

"Adaptive Filter Theory" looks at both the mathematical theory behind various linear adaptive filters with finite-duration impulse response (FIR) and the elements of supervised neural networks. Up-to-date and in-depth treatment of adaptive filters develops concepts in a unified and accessible manner. This highly successful book provides comprehensive coverage of adaptive filters in a highly readable and understandable fashion. Includes an extensive use of illustrative examples; and MATLAB experiments, which illustrate the practical realities and intricacies of adaptive filters, the codes for which can be downloaded from the Web. Covers a wide range of topics including Stochastic Processes, Wiener Filters, and Kalman Filters. For those interested in learning about adaptive filters and the theories behind them.

For courses in Wireless Communication.This text provides a self-motivating introduction to wireless communications; it presents topics in a manner consistent with their natural evolution, based on the principle of increasing spectral efficiency of the radio transmission. Wireless Systems begins with a discussion of FDMA systems and follows the evolution through TDMA, CDMA, and SDMA techniques. Engineering principles required for each multiple access strategy are presented parallel with it.