Neural Networks and Qualitative Physics: A Viability Approach

This book is devoted to some mathematical methods that arise in two domains of artificial intelligence: neural networks and qualitative physics. Professor Aubin makes use of control and viability theory in neural networks and cognitive systems, regarded as dynamical systems controlled by synaptic matrices, and set-valued analysis that plays a natural and crucial role in qualitative analysis and simulation. This allows many examples of neural networks to be presented in a unified way. In addition, several results on the control of linear and nonlinear systems are used to obtain a "learning algorithm" of pattern classification problems, such as the back-propagation formula, as well as learning algorithms of feedback regulation laws of solutions to control systems subject to state constraints.

Author: Jean-Pierre Aubin
Publisher: Cambridge University Press
Published: 08/11/2011
Pages: 302
Binding Type: Paperback
Weight: 0.89lbs
Size: 9.00h x 6.00w x 0.63d
ISBN: 9781107402843

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