<p><p>The book reports on the latest theories on artificial neural networks, with a special emphasis on bio-neuroinformatics methods. It includes twenty-three papers selected from among the best contributions on bio-neuroinformatics-related issues, which were presented at the International Conferenc
Artificial Neural Networks: Methods and Applications
β Scribed by Hugh M. Cartwright B.Sc, PhD (auth.), David J. Livingstone (eds.)
- Publisher
- Humana Press
- Year
- 2009
- Tongue
- English
- Leaves
- 258
- Series
- Methods in Molecular Biologyβ’ 458
- Edition
- 1
- Category
- Library
No coin nor oath required. For personal study only.
β¦ Synopsis
As an extension of artificial intelligence research, artificial neural networks (ANN) aim to simulate intelligent behavior by mimicking the way that biological neural networks function. In Artificial Neural Networks, an international panel of experts report the history of the application of ANN to chemical and biological problems, provide a guide to network architectures, training and the extraction of rules from trained networks, and cover many cutting-edge examples of the application of ANN to chemistry and biology. In the tradition of the highly successful Methods in Molecular Biologyβ’ series, this volume exhibits clear, easy-to-use information with many step-by-step laboratory protocols.
Comprehensive and state-of-the-art, Artificial Neural Networks is an excellent guide to this accelerating technological field of study.
β¦ Table of Contents
Front Matter....Pages i-x
Back Matter....Pages 1-13
....Pages 14-22
β¦ Subjects
Neurosciences; Computer Science, general; Artificial Intelligence (incl. Robotics)
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In this book, international experts report the history of the application of ANN to chemical and biological problems, provide a guide to network architectures, training and the extraction of rules from trained networks, and cover many cutting-edge examples of the application of ANN to chemistry and
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Thorough, compact, and self-contained, this explanation and analysis of a broad range of neural nets is conveniently structured so that readers can first gain a quick global understanding of neural nets -- <I>without</I></B> the mathematics -- and can then delve into mathematical specifics as necess
Thorough, compact, and self-contained, this explanation and analysis of a broad range of neural nets is conveniently structured so that readers can first gain a quick global understanding of neural nets - without the mathematics - and can then delve into mathematical specifics as necessary. The beha