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| Preface | ||
| I | Introduction | 1 |
| 1 | Introduction | 3 |
| 2 | Bifurcations in Neuron Dynamics | 25 |
| 3 | Neural Networks | 103 |
| 4 | Introduction to Canonical Models | 111 |
| II | Derivation of Canonical Models | 141 |
| 5 | Local Analysis of WCNNs | 143 |
| 6 | Local Analysis of Singularly Perturbed WCNNs | 189 |
| 7 | Local Analysis of Weakly Connected Maps | 209 |
| 8 | Saddle-Node on a Limit Cycle | 219 |
| 9 | Weakly Connected Oscillators | 247 |
| III | Analysis of Canonical Models | 295 |
| 10 | Multiple Andronov-Hopf Bifurcation | 297 |
| 11 | Multiple Cusp Bifurcation | 311 |
| 12 | Quasi-Static Bifurcations | 337 |
| 13 | Synaptic Organizations of the Brain | 353 |
| References | 381 | |
| Index | 395 |
| Price | Condition | Delivery | Seller | Action |
| $100.09 | Digital |
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Add Weakly Connected Neural Networks, Weakly Connected Neural Networks is devoted to local and global analysis of weakly connected systems with applications to neurosciences. Using bifurcation theory and canonical models as the major tools of analysis, it presents systematic and well-motivate, Weakly Connected Neural Networks to the inventory that you are selling on WonderClubX
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Add Weakly Connected Neural Networks, Weakly Connected Neural Networks is devoted to local and global analysis of weakly connected systems with applications to neurosciences. Using bifurcation theory and canonical models as the major tools of analysis, it presents systematic and well-motivate, Weakly Connected Neural Networks to your collection on WonderClub |