MATLAB and Simulink Based Books

Neural Network Design 2730

Neural Network Design

This text provides a clear and detailed survey of basic neural network architectures and learning rules. The authors emphasize mathematical analysis of networks, methods for training networks, and application of networks to practical engineering problems in pattern recognition, signal processing, and control systems. Background material, such as linear algebra, optimization, and stability, is provided. Simple building blocks are used to explain associative and competitive networks. They include feature maps, learning vector quantization, and adaptive resonance theory. Examples and solved problems are included with optional exercises incorporating the use of MATLAB.  An instructor's manual is available for adopters of this text.

To obtain a copy of the Neural Network Design text or the Instructors Manual contact John Stovall at the University of Colorado Bookstore, phone 303-492-3648. Ask specifically for an instructor's manual if you are instructing a class and want one.

Companion software available In addition, a set of MATLAB code files, transparency masters, and a set of video lectures are available. Retrieve companion software

무료 알고리즘 개발 기술자료 키트

C, C++ 또는 Fortran과 같은 로우 레벨(low-level) 언어를 사용하는 것보다 MATLAB을 사용해 알고리즘을 개발하는 것이 훨씬 빠른 이유를 확인해 보십시오.

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About This Book

Martin T. HaganOklahoma State University
Howard B. DemuthUniversity of Idaho
Mark Hudson BealeMHB, Inc

Martin/Hagan (Distributed by the University of Colorado), 1996

ISBN: 0-9717321-0-8
Language: English