Fast Computation with Neural Oscillators

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dc.creatorWang, Wei
dc.creatorSlotine, Jean-Jacques E.
dc.date2003-12-17
dc.date.accessioned2026-07-07T05:58:04Z
dc.date.available2026-07-07T05:58:04Z
dc.descriptionArtificial 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.
dc.description7 pages, 5 figures
dc.identifierhttps://arxiv.org/abs/q-bio/0312025
dc.identifierhttp://arxiv.org/abs/q-bio/0312025
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/88220
dc.subjectNeurons and Cognition
dc.titleFast Computation with Neural Oscillators
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