Neural networks and qualitative physics / Jean-Pierre Aubin.
By: Aubin, Jean Pierre.
Material type: BookPublisher: Cambridge. New York : Cambridge University Press, 1996Description: xvii, 283 p. : ill. ; 24 cm.ISBN: 0521445329 .Subject(s): Artificial intelligence -- Mathematics | Neural networks (Computer science) | Mathematical physicsDDC classification: 006.3Item type | Current library | Call number | Copy number | Status | Date due | Barcode | Item holds |
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General Lending | MTU Bishopstown Library Lending | 006.3 (Browse shelf(Opens below)) | 1 | Available | 00014469 |
Enhanced descriptions from Syndetics:
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.
Bibliography: (pages 262-279) and index.
Neural networks: A control approach -- Pseudoinverses and tensor products -- Associate memories -- The gradient method -- Nonlinear neural networks -- External learning algorithm for feedback controls -- Learning processes of cognitive systems -- Qualitative analysis of static problems -- Dynamical qualitative simulation.
Table of contents provided by Syndetics
- 1 Neural networks: a control approach
- 2 Pseudo-inverses and tensor products
- 3 Associative memories
- 4 The gradient method
- 5 Nonlinear neural networks
- 6 External learning algorithm of feedback controls
- 7 Internal learning algorithm of feedback controls
- 8 Learning processes of cognitive systems
- 9 Qualitative analysis of static problems
- 10 Dynamical qualitative simulation
- Appendix A Convex and nonsmooth analysis
- Appendix B Control of an AUV