| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 785703 | International Journal of Non-Linear Mechanics | 2012 | 6 Pages |
Abstract
⺠We model electrically and chemically coupled learning neuronal networks with small-world connectivity. ⺠The variation properties of synaptic weights are examined. ⺠The effects of the synaptic learning rate on the properties of firing rate and synchronization are investigated. ⺠It is found that synaptic learning suppresses over-excitement for the networks.
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Authors
F. Han, Q.S. Lu, M. Wiercigroch, J.A. Fang, Z.J. Wang,