Please use this identifier to cite or link to this item: http://hdl.handle.net/2440/28989
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Type: Conference paper
Title: Neural mechanisms for analog to digital conversion
Author: McDonnell, M.
Abbott, D.
Pearce, C.
Citation: BioMEMS and nanotechnology : 10-12 December 2003, Perth, Australia / Dan V. Nicolau, Uwe R. Muller, John M. Dell (eds.), pp. 278-286
Publisher: SPIE
Publisher Place: CD-ROM
Issue Date: 2004
Series/Report no.: Proceedings of SPIE--the International Society for Optical Engineering ; 5275.
ISBN: 0-8194-5168-1
ISSN: 0277-786X
Conference Name: BioMEMS and Nanotechnology (1st : 2003 : Perth, Australia)
Statement of
Responsibility: 
Mark D. McDonnell, Derek Abbott, and Charles E. Pearce
Abstract: Consider an array of threshold devices, such as neurons orcomparators, where each device receives the same input signal, butis subject to independent additive noise. When the output fromeach device is summed to give an overall output, the system actsas a noisy Analog to Digital Converter (ADC). Recently, such asystem was analyzed in terms of information theory, and it wasshown that under certain conditions the transmitted informationthrough the array is maximized for non-zero noise. Such aphenomenon where noise can be of benefit in a nonlinear system istermed Stochastic Resonance (SR). The effect in the array ofthreshold devices was termed Suprathreshold Stochastic Resonance(SSR) to distinguish it from conventional forms of SR, in whichusually a signal needs to be subthreshold for the effect to occur.In this paper we investigate the efficiency of the analog todigital conversion when the system acts like an array of simple neurons, by analyzing the average distortion incurred and comparing this distortion to that of a conventional flash ADC.
Description: © 2004 COPYRIGHT SPIE--The International Society for Optical Engineering.
RMID: 0020040780
DOI: 10.1117/12.523165
Appears in Collections:Applied Mathematics publications

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