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Title:Neural Networks And Learning Machines
Format Type:Ebook
Author:Simon Haykin
Publisher:Pearson Education
ISBN 13:
Number of Pages:864
Category:Artificial intelligence, Computer science, Unfinished

Neural Networks And Learning Machines by Simon Haykin

PDF, EPUB, MOBI, TXT, DOC Neural Networks And Learning Machines No description available

Neural Networks: A Comprehensive Foundation

Introducing students to the many facets of neural networks this text provides many case studies to illustrate their real life practical applications

Communication Systems

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

Signals and Systems

The text provides motivation for students to learn because they ll discover how various concepts relate to the engineering profession through these real world examples of signals and systems An abundant use of examples and drill problems are integrated throughout so they ll be able to master the material And a large number of end of chapter problems are provided to help solidify the concepts

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

Adaptive Filter Theory

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

An Introduction to Analog and Digital Communications

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 receiver of a communication system Readers will next learn about electrical noise and then progress to multiplexing and multiple access techniques

Neural Networks And Learning Machines

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Kalman Filtering and Neural Networks

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

Modern Wireless Communications

b b This book 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 b TOPICS b i Wireless Systems i begins with a discussion of FDMA systems and follows with the evolution through TDMA CDMA and SDMA techniques Engineering principles required for each multiple access strategy are presented parallel to it b b For electrical engineers and others involved in wireless communications

Least-Mean-Square Adaptive Filters

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

An Introduction to Analog and Digital Communications, Modern Wireless Communications, Signals and Systems, Kalman Filtering and Neural Networks, Neural Networks And Learning Machines, Adaptive Filter Theory, Communication Systems, Least-Mean-Square Adaptive Filters, Neural Networks: A Comprehensive Foundation, Digital Communications