| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 411007 | Neurocomputing | 2006 | 7 Pages |
Abstract
This paper studies new spike-based models for winner-take-all computation and coincidence detection. In both cases, fast convergence is achieved independent of initial conditions, and network complexity is linear in the number of inputs. Fully distributed versions can be modelled based on groups of interneurons connected through electrical synapses.
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
Wei Wang, Jean-Jacques E. Slotine,