dorsal/arxiv
View SchemaFast Computation with Neural Oscillators
| Authors | Wei Wang, Jean-Jacques E. Slotine |
|---|---|
| Categories | |
| ArXiv ID | q-bio/0312025 |
| URL | https://arxiv.org/abs/q-bio/0312025 |
Abstract
Artificial spike-based computation, inspired by models of computations in the central nervous system, may present significant performance advantages over traditional methods for specific types of large scale problems. In this paper, we study new models for two common instances of such computation, winner-take-all and coincidence detection. In both cases, very fast convergence is achieved independent of initial conditions, and network complexity is linear in the number of inputs.
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"abstract": "Artificial spike-based computation, inspired by models of computations in the\ncentral nervous system, may present significant performance advantages over\ntraditional methods for specific types of large scale problems. In this paper,\nwe study new models for two common instances of such computation,\nwinner-take-all and coincidence detection. In both cases, very fast convergence\nis achieved independent of initial conditions, and network complexity is linear\nin the number of inputs.",
"arxiv_id": "q-bio/0312025",
"authors": [
"Wei Wang",
"Jean-Jacques E. Slotine"
],
"categories": [
"q-bio.NC"
],
"title": "Fast Computation with Neural Oscillators",
"url": "https://arxiv.org/abs/q-bio/0312025"
},
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