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Book Categories |
| Preface | ||
| Notations | ||
| Introduction | 1 | |
| 1 | Basic Tools | 27 |
| 2 | Probability Estimation and Pattern Classification | 57 |
| 3 | Nonlinear Time-Series Prediction | 75 |
| 4 | Nonlinear State Estimation | 115 |
| 5 | Dynamic Reconstruction of Chaotic Processes | 137 |
| 6 | Discussion | 155 |
| App. of Notes to the Text | 171 | |
| References | 177 | |
| Index | 189 |
| Price | Condition | Delivery | Seller | Action |
| $133.11 | Digital |
| WonderClub |
Stephen Corak
reviewed Regularized Radial Basis Function Networks: Theory and Applications on October 28, 2018
Regularized Radial Basis Function Networks: Theory and Applications
Most books about neural networks are silent when it comes to less obvious details of what training feedforward networks actually does, and what the result of the network represents. This book analyzes all these details by means of statistics, and consequently gives a very solid foundation for understanding neural networks. The definitive book for feedforward neural networks - extremely good! The math-heavy treatise makes it unsuitable for a beginners book, though.
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Add Regularized Radial Basis Function Networks: Theory and Applications, Simon Haykin is a well-known author of books on neural networks. * An authoritative book dealing with cutting edge technology. * This book has no competition., Regularized Radial Basis Function Networks: Theory and Applications to the inventory that you are selling on WonderClubX
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Add Regularized Radial Basis Function Networks: Theory and Applications, Simon Haykin is a well-known author of books on neural networks. * An authoritative book dealing with cutting edge technology. * This book has no competition., Regularized Radial Basis Function Networks: Theory and Applications to your collection on WonderClub |