Aimed at senior undergraduate or first-year graduate courses in neural networks and neurocomputing, this work 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.
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Aimed at senior undergraduate or first-year graduate courses in neural networks and neurocomputing, this work 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.
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