Please use this identifier to cite or link to this item: https://hdl.handle.net/2440/28990
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Type: Conference paper
Title: Optimal quantization for energy-efficient information transfer in a population of neuron-like devices
Author: McDonnell, M.
Stocks, N.
Pearce, C.
Abbott, D.
Citation: Noise in complex systems and stochastic dynamics II : 26-28 May, 2004, Maspalomas, Gran Canaria, Spain / Zoltán Gingl (ed.), pp. 222-232
Publisher: SPIE
Publisher Place: CD-ROM
Issue Date: 2004
Series/Report no.: Proceedings of SPIE--the International Society for Optical Engineering ; 5471.
ISBN: 0-8194-5393-5
ISSN: 0277-786X
1996-756X
Conference Name: Fluctuations and Noise (2004 : Gran Canaria Island, Spain)
Editor: Kish, L.
Statement of
Responsibility: 
Mark D. McDonnell, Nigel G. Stocks, Charles E. M. Pearce, and Derek Abbott
Abstract: Suprathreshold Stochastic Resonance (SSR) is a recently discoveredform of stochastic resonance that occurs in populations of neuron-like devices. A key feature of SSR is that all devices in the population possess identical threshold nonlinearities. It haspreviously been shown that information transmission through such asystem is optimized by nonzero internal noise. It is also clearthat it is desirable for the brain to transfer information in anenergy efficient manner. In this paper we discuss the energy efficient maximization of information transmission for the case ofvariable thresholds and constraints imposed on the energy available to the system, as well as minimization of energy for the case of a fixed information rate. We aim to demonstrate that under certain conditions, the SSR configuration of all devices having identical thresholds is optimal. The novel feature of this work is that optimization is performed by finding the optimal threshold settings for the population of devices, which is equivalent to solving a noisy optimal quantization problem.
Description: © 2004 COPYRIGHT SPIE--The International Society for Optical Engineering
DOI: 10.1117/12.546934
Published version: http://dx.doi.org/10.1117/12.546934
Appears in Collections:Applied Mathematics publications
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