Neural Networks and Qualitative Physics : A Viability Approach
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Book Description
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.
Neural Networks and Qualitative Physics: A Viability Approach,Jean-Pierre Aubin,Cambridge University Press,0521445329,Artificial Intelligence - General,Artificial intelligence,Computers - General Information,Mathematical physics,Mathematics,Neural Computing,Neural networks (Computer scie,Neural networks (Computer science),Physics,Probability & Statistics - General,Science/Mathematics,Artificial intelligence--Mathematics,Mathematics / Differential Equations,Probability & statistics
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