Principles of Neurocomputing for Science and Engineering by Fredric M. Ham

Cover of: Principles of Neurocomputing for Science and Engineering | Fredric M. Ham

Published by McGraw-Hill Science/Engineering/Math .

Written in English

Read online

Subjects:

  • Mathematics for scientists & engineers,
  • Neural Networks,
  • Neural networks (Computer science),
  • Technology,
  • Technology & Industrial Arts,
  • Textbooks,
  • Science/Mathematics,
  • Computer Engineering,
  • Engineering - Electrical & Electronic,
  • Computers / Networking / General,
  • Networks,Neural Networks,Neurocomputing,Solving Matrix Algebra,Optimization Problems,Temporal Feedforward Networks,Recurrent Networks,Self-Organizing Networks,Mapping Networks,Fundamental Neurocomputing Concepts,Engineering,Statistical Methods,
  • Neural computers,
  • Neural networks (Computer scie

Book details

The Physical Object
FormatHardcover
Number of Pages672
ID Numbers
Open LibraryOL9249665M
ISBN 100070259666
ISBN 109780070259669

Download Principles of Neurocomputing for Science and Engineering

Start with hagan neural network design and then ham principles of neurocomputing If you know some concepts: Start directly with this book and refer to each and every research paper given as reference in this by: For each neurocomputing concept, a solid mathematical foundation is presented along with illustrative examples to accompany that particular architecture and associated training algorithm.

It incorporates many detailed Unlike other neural network books, this is written specifically for scientists and engineers who want to apply neural networks to solve complex problems/5.

For each neurocomputing concept,a solid mathematical foundation is presented along with illustrative examples to accompany that particular architecture and associated training algorithm.

The book is primarily intended for graduate-level neural networks courses,but in some instances may be used at the undergraduate level.

* Unlike other neural network books, this is written specifically for scientists and engineers who want to apply neural networks to solve complex problems * For each neurocomputing concept, a solid mathematical foundation is presented along with illustrative examples to accompany that particular architecture and associated training algorithm/5(10).

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Principles of Neurocomputing for Science and Engineering by Fredric M. Ham, Ivica Kostanic, Ham Fredric Hardcover Book, pages See Other Available Editions Description * Unlike other neural network books, this is written specifically for scientists and engineers who want to apply neural networks to solve complex ries: Neural Networks.

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It is a vast discipline of research that mainly includes neuroscience, machine learning, searching and knowledge : Bipin Kumar Tripathi. Details 1. Introduction to Neurocomputing -- 2.

Fundamental Neurocomputing Concepts -- 3. Mapping Networks -- 4. Self-Organizing Networks -- 5. Recurrent Networks and Temporal Feedforward Networks -- 6. Neural Networks for Optimization Problems -- 7. Solving Matrix Algebra Problems with Neural.

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– 14), divided by the number of documents in these three previous years (e.g. – 14). Principles of Neurocomputing for Science and Engineering, Fredric M.

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Neurocomputing Software Track publishes a new format, the Original Software Publication (OSP) to disseminate exiting and useful software in the areas of neural networks and learning systems, including, but not restricted to, architectures, learning methods, analysis of network dynamics, theories of learning, self-organization, biological neural.

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McGraw-Hill, New York () Google ScholarCited by: 2.

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