Please use this identifier to cite or link to this item: http://hdl.handle.net/2440/22817
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Type: Journal article
Title: Optimal information transmission in nonlinear arrays through suprathreshold stochastic resonance
Author: McDonnell, M.
Stocks, N.
Pearce, C.
Abbott, D.
Citation: Physics Letters A, 2006; 352(3):183-189
Publisher: Elsevier Science BV
Issue Date: 2006
ISSN: 0375-9601
Statement of
Responsibility: 
Mark D. McDonnell, Nigel G. Stocks, Charles E.M. Pearce and Derek Abbott
Abstract: We examine the optimal threshold distribution in populations of noisy threshold devices. When the noise on each threshold is independent, and sufficiently large, the optimal thresholds are realized by the suprathreshold stochastic resonance effect, in which case all threshold devices are identical. This result has relevance for neural population coding, as such noisy threshold devices model the key dynamics of nerve fibres. It is also relevant to quantization and lossy source coding theory, since the model provides a form of stochastic signal quantization. Furthermore, it is shown that a bifurcation pattern appears in the optimal threshold distribution as the noise intensity increases. Fisher information is used to demonstrate that the optimal threshold distribution remains in the suprathreshold stochastic resonance configuration as the population size approaches infinity.
Keywords: Information theory; neural coding; suprathreshold stochastic resonance; quantization; optimal quantization; population coding; bifurcations; point density function
RMID: 0020060223
DOI: 10.1016/j.physleta.2005.11.068
Description (link): http://www.elsevier.com/wps/find/journaldescription.cws_home/505705/description#description
Appears in Collections:Electrical and Electronic Engineering publications

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