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Learning and Generalisation: With Applications to Neural Networks

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Learning and Generalisation: With Applications to Neural Networks - Vidyasagar, Mathukumalli
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Learning and Generalization provides a formal mathematical theory addressing intuitive questions of the type: * How does a machine learn a concept on the basis of examples? * How can a neural network, after training, correctly predict the outcome of a previously unseen input? * How much training is required to achieve a given level of accuracy in the prediction? * How can one identify the dynamical behaviour of a nonlinear control system by observing its input-output behaviour over a finite time? The second edition covers ...

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Learning and Generalisation: With Applications to Neural Networks 2010, Springer London Ltd, England

ISBN-13: 9781849968676

Softcover reprint of hardcover 2nd edition 2002

Paperback

Learning and Generalisation: With Applications to Neural Networks 2002, Springer, London

ISBN-13: 9781852333737

2nd 2002 edition

Hardcover