Weakly connected neural networks

I. Introduction. 1. Introduction. 2. Bifurcations in Neuron Dynamics. 3. Neural Networks. 4. Introduction to Canonical Models -- II. Derivation of Canonical Models. 5. Local Analysis of WCNNs. 6. Local Analysis of Singularly Perturbed WCNNs. 7. Local Analysis of Weakly Connected Maps. 8. Saddle-Node...

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1. Verfasser:	Hoppensteadt, Frank C. (VerfasserIn)
Weitere Verfasser:	Ižikevič, Eugene M. (BerichterstatterIn), Izhikevich, Eugene M. (BerichterstatterIn)
Format:	UnknownFormat
Sprache:	eng
Veröffentlicht:	New York, Heidelberg u.a. Springer 1997
Schriftenreihe:	Applied mathematical sciences 126
Schlagworte:	Neural networks (Computer science) > Lehrbuch > Nervennetz > Mathematisches Modell > Verzweigung
Online Zugang:	Inhaltsverzeichnis Inhaltstext Table of contents only
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Zusammenfassung:	I. Introduction. 1. Introduction. 2. Bifurcations in Neuron Dynamics. 3. Neural Networks. 4. Introduction to Canonical Models -- II. Derivation of Canonical Models. 5. Local Analysis of WCNNs. 6. Local Analysis of Singularly Perturbed WCNNs. 7. Local Analysis of Weakly Connected Maps. 8. Saddle-Node on a Limit Cycle. 9. Weakly Connected Oscillators -- III. Analysis of Canonical Models. 10. Multiple Andronov-Hopf Bifurcation. 11. Multiple Cusp Bifurcation. 12. Quasi-Static Bifurcations. 13. Synaptic Organizations of the Brain. Literaturverz. S. [381] - 393 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-motivated development of both weakly connected system theory and mathematical neuroscience. Weakly Connected Neural Networks will be useful to researchers and graduate students in various branches of mathematical neuroscience 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-motivated development of both weakly connected system theory and mathematical neuroscience. Weakly Connected Neural Networks will be useful to researchers and graduate students in various branches of mathematical neuroscience
Beschreibung:	Literaturverz. S. 381 - 393
Beschreibung:	XVI, 400 S. graph. Darst. 25 cm
ISBN:	0387949488 0-387-94948-8