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An Introduction to Neural Networks (Bradford Books)
 
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An Introduction to Neural Networks (Bradford Books) (Hardcover)

by J A Anderson (Author)
5.0 out of 5 stars  See all reviews (1 customer review)
RRP: £96.95
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Product details

  • Hardcover: 672 pages
  • Publisher: MIT Press (2 May 1995)
  • Language English
  • ISBN-10: 0262011441
  • ISBN-13: 978-0262011440
  • Product Dimensions: 26.4 x 21.3 x 3.6 cm
  • Average Customer Review: 5.0 out of 5 stars  See all reviews (1 customer review)
  • Amazon.co.uk Sales Rank: 2,440,907 in Books (See Bestsellers in Books)

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Product Description

Product Description

Based on notes that have been class-tested for more than a decade, this text is aimed at cognitive science and neuroscience students who need to understand brain function in terms of computational modelling and at engineers who want to go beyond formal algorithms to applications and computing strategies. It offers an approach networks from a broad neuroscience and cognitive science perspective, with an emphasis on the biology and psychology behind the assumptions of the models, as well as on what the models might be used for. It describes the mathematical and computational tools needed and provides an account of the author's own ideas. Students learn how to teach arithmetic to a neural network and get a short course on linear associative memory and adaptive maps. They are introduced to the author's brain-state-in-a-box (BSB) model and are provided with some of the neurobiological background necessary for a firm grasp of the general subject.

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4 of 4 people found the following review helpful:
5.0 out of 5 stars Amazing Neural Net Introduction!, 30 Jul 1998
By A Customer
This is one of the best books I have ever read. It introduces neural networks, with a strong emphasis on biological plausibility. For example, the book compares the visual systems of simple animals with neural network feature extraction. Anderson moves effectively among evolutionary biology, cognitive science, artificial intelligence, and behavioral psychology. His insights are important, clear, and often funny as well. The book gently introduces source code for implementing the various neural networks that he describes.
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