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The re-emergence of network-based approaches to artificial intelligence has been accomplished by an explosion of research spanning a wide range of disciplines, among them cognitive science, computer science, biology, neuroscience, electrical engineering, psychology, econometrics, and philosophy. This collection of papers presents a rigorous mathematical analysis of the approximation and learning capabilities of the leading class of single hidden layer feedforward networks. Annotation copyright Book News, Inc. Portland, Or.
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Artificial Neural Networks: Approximation and Learning Theory
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