Neural Networks and Qualitative Physics A Viability Approach
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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.
| Publisher Name | Cambridge University Press |
|---|---|
| Author Name | Hagendorf, Col |
| Format | Audio |
| Bisac Subject Major | MAT |
| Language | NG |
| Isbn 10 | 1107402840 |
| Isbn 13 | 9781107402843 |
| Target Age Group | min:NA, max:NA |
| Dimensions | 00.90" H x 00.06" L x 00.00" W |
| Page Count | 302 |
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