Weakly Connected Neural Networks:
Saved in:
| Main Author: | |
|---|---|
| Format: | Electronic eBook |
| Language: | English |
| Published: |
New York, NY
Springer New York
1997
|
| Series: | Applied Mathematical Sciences
126 |
| Subjects: | |
| Online Access: | Volltext |
| Item Description: | This book is devoted to an analysis of general weakly connected neural networks (WCNNs) that can be written in the form (0.1) m Here, each Xi E IR is a vector that summarizes all physiological attributes of the ith neuron, n is the number of neurons, Ii describes the dynam ics of the ith neuron, and gi describes the interactions between neurons. The small parameter € indicates the strength of connections between the neurons. Weakly connected systems have attracted much attention since the sec ond half of seventeenth century, when Christian Huygens noticed that a pair of pendulum clocks synchronize when they are attached to a light weight beam instead of a wall. The pair of clocks is among the first weakly connected systems to have been studied. Systems of the form (0.1) arise in formal perturbation theories developed by Poincare, Liapunov and Malkin, and in averaging theories developed by Bogoliubov and Mitropolsky |
| Physical Description: | 1 Online-Ressource (XVI, 402 p) |
| ISBN: | 9781461218289 9781461273028 |
| ISSN: | 0066-5452 |
| DOI: | 10.1007/978-1-4612-1828-9 |
Staff View
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| spelling | Hoppensteadt, Frank C. Verfasser aut Weakly Connected Neural Networks by Frank C. Hoppensteadt, Eugene M. Izhikevich New York, NY Springer New York 1997 1 Online-Ressource (XVI, 402 p) txt rdacontent c rdamedia cr rdacarrier Applied Mathematical Sciences 126 0066-5452 This book is devoted to an analysis of general weakly connected neural networks (WCNNs) that can be written in the form (0.1) m Here, each Xi E IR is a vector that summarizes all physiological attributes of the ith neuron, n is the number of neurons, Ii describes the dynam ics of the ith neuron, and gi describes the interactions between neurons. The small parameter € indicates the strength of connections between the neurons. Weakly connected systems have attracted much attention since the sec ond half of seventeenth century, when Christian Huygens noticed that a pair of pendulum clocks synchronize when they are attached to a light weight beam instead of a wall. The pair of clocks is among the first weakly connected systems to have been studied. Systems of the form (0.1) arise in formal perturbation theories developed by Poincare, Liapunov and Malkin, and in averaging theories developed by Bogoliubov and Mitropolsky Mathematics Neurosciences Global analysis (Mathematics) Analysis Mathematical and Computational Biology Mathematik Mathematisches Modell (DE-588)4114528-8 gnd rswk-swf Neuronales Netz (DE-588)4226127-2 gnd rswk-swf Nervennetz (DE-588)4041638-0 gnd rswk-swf Nervennetz (DE-588)4041638-0 s Mathematisches Modell (DE-588)4114528-8 s 1\p DE-604 Neuronales Netz (DE-588)4226127-2 s 2\p DE-604 Izhikevich, Eugene M. Sonstige oth https://doi.org/10.1007/978-1-4612-1828-9 Verlag Volltext 1\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk 2\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk |
| spellingShingle | Hoppensteadt, Frank C. Weakly Connected Neural Networks Mathematics Neurosciences Global analysis (Mathematics) Analysis Mathematical and Computational Biology Mathematik Mathematisches Modell (DE-588)4114528-8 gnd Neuronales Netz (DE-588)4226127-2 gnd Nervennetz (DE-588)4041638-0 gnd |
| subject_GND | (DE-588)4114528-8 (DE-588)4226127-2 (DE-588)4041638-0 |
| title | Weakly Connected Neural Networks |
| title_auth | Weakly Connected Neural Networks |
| title_exact_search | Weakly Connected Neural Networks |
| title_full | Weakly Connected Neural Networks by Frank C. Hoppensteadt, Eugene M. Izhikevich |
| title_fullStr | Weakly Connected Neural Networks by Frank C. Hoppensteadt, Eugene M. Izhikevich |
| title_full_unstemmed | Weakly Connected Neural Networks by Frank C. Hoppensteadt, Eugene M. Izhikevich |
| title_short | Weakly Connected Neural Networks |
| title_sort | weakly connected neural networks |
| topic | Mathematics Neurosciences Global analysis (Mathematics) Analysis Mathematical and Computational Biology Mathematik Mathematisches Modell (DE-588)4114528-8 gnd Neuronales Netz (DE-588)4226127-2 gnd Nervennetz (DE-588)4041638-0 gnd |
| topic_facet | Mathematics Neurosciences Global analysis (Mathematics) Analysis Mathematical and Computational Biology Mathematik Mathematisches Modell Neuronales Netz Nervennetz |
| url | https://doi.org/10.1007/978-1-4612-1828-9 |
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