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NEURAL NETWORK FUNDAMENTALS WITH GRAPHS, ALGORITHM


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Sinopse

This text is aimed at senior or first year graduate courses in neural networks and neurocomputing within various departments of engineering, computer science and mathematics. The text presents neural network theory for diverse applications in a unified way, where the structures of artificial neural networks are characterized by distinguished classes of graphs. The book proceeds from a clear but concise exposition of neuroscience fundamentals, graph theory and algorithms to a detailed analysis of perception and Ims-theory based neural networks, multilayer feedforward networks, and self-organizing and competitive learning neural networks. The text culminates with a chapter on selected applications.

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