Fast computation with neural oscillators

descriptionPublicationkeyboard_double_arrow_right Article , Preprint 01 Oct 2006Embargo end date: 01 Jan 2003 English Publisher:Elsevier BVJournal:Neurocomputing, volume 69, pages 2,320-2,326 (issn: 0925-2312,

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Authors: Wei Wang 0008; Jean-Jacques E. Slotine;

doi: 10.1016/j.neucom.2005.04.012 , 10.48550/arxiv.q-bio/0312025

arXiv: q-bio/0312025

Fast computation with neural oscillators

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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.

7 pages, 5 figures

Related Organizations

Massachusetts Institute of Technology
United States

Keywords

Quantitative Biology - Neurons and Cognition, FOS: Biological sciences, Neurons and Cognition (q-bio.NC)

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