Awards

• Winner of <i>Choice</i> Outstanding Academic Title, 1996. 1996
• Winner of <PrizeName>Choice Outstanding Academic Title, 1996.</PrizeName> 1996
• Winner of Choice Outstanding Academic Title, 1996. 1996
• Winner of Choice Outstanding Academic Title, 1996.</PrizeName> 1996

Overview

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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9780262510813

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James A. Anderson is Professor in the Department of Cognitive and Linguistic Sciences at Brown University.

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