Mathematical Methods for Neural Network Analysis and Design

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For convenience, many of the proofs of the key theorems have been rewritten so that the entire book uses a relatively uniform notion.

Mathematical Approaches to Neural Networks

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The subject of Neural Networks is being seen to be coming of age, after its initial inception 50 years ago in the seminal work of McCulloch and Pitts. It is pro

Deep Learning Architectures

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This book describes how neural networks operate from the mathematical point of view. As a result, neural networks can be interpreted both as function universal

Dynamics of Neural Networks

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This book treats essentials from neurophysiology (Hodgkin–Huxley equations, synaptic transmission, prototype networks of neurons) and related mathematical con

Mathematical Perspectives on Neural Networks

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Recent years have seen an explosion of new mathematical results on learning and processing in neural networks. This body of results rests on a breadth of mathem