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Digital Communications (Rating: 3.57 - 2144 votes)

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Title:Digital Communications
Format Type:Ebook
Author:
Publisher:Wiley
ISBN:0471629472
ISBN 13:
Number of Pages:624
Category:Manga

Digital Communications by Simon Haykin

PDF, EPUB, MOBI, TXT, DOC Digital Communications 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

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Communication Systems, An Introduction to Analog and Digital Communications, Least-Mean-Square Adaptive Filters, Signals and Systems, Neural Networks: A Comprehensive Foundation, Adaptive Filter Theory, Kalman Filtering and Neural Networks, Modern Wireless Communications, Digital Communications, Neural Networks And Learning Machines
b State of the art coverage of Kalman filter methods for the design of neural networks b This self contained book consists of seven chapters by expert contributors that discuss Kalman filtering as applied to the training and use of neural networks Although the traditional approach to the subject is almost always linear this book recognizes and deals with the fact that real problems are most often nonlinear br br The first chapter offers an introductory treatment of Kalman filters with an emphasis on basic Kalman filter theory Rauch Tung Striebel smoother and the extended Kalman filter Other chapters cover br br br An algorithm for the training of feedforward and recurrent multilayered perceptrons based on the decoupled extended Kalman filter DEKF Applications of the DEKF learning algorithm to the study of image sequences and the dynamic reconstruction of chaotic processes The dual estimation problem Stochastic nonlinear dynamics the expectation maximization EM algorithm and the extended Kalman smoothing EKS algorithm The unscented Kalman filter Each chapter with the exception of the introduction includes illustrative applications of the learning algorithms described here some of which involve the use of simulated and real life data Kalman Filtering and Neural Networks serves as an expert resource for researchers in neural networks and nonlinear dynamical systems br br An Instructor s Manual presenting detailed solutions to all the problems in the book is available upon request from the Wiley Makerting Department, Edited by the original inventor of the technology Includes contributions by the foremost experts in the field The only book to cover these topics together, Examines both the mathematical theory behind various linear adaptive filters with finite duration impulse response and the elements of supervised neural networks The fourth edition of this book has been updated and refined to stay current with the field, This best selling easy to read communication systems text has been extensively revised to include the most exhaustive treatment of digital communications in an undergraduate level text In addition to being the most up to date communications text available Simon Haykin has added MATLAB computer experiments