Neural mechanisms for analog to digital conversion
Date
2004
Authors
McDonnell, M.
Abbott, D.
Pearce, C.
Editors
Faraone, L.
Varadan, V.K.
Varadan, V.K.
Advisors
Journal Title
Journal ISSN
Volume Title
Type:
Conference paper
Citation
BioMEMS and nanotechnology : 10-12 December 2003, Perth, Australia / Dan V. Nicolau, Uwe R. Muller, John M. Dell (eds.), pp. 278-286
Statement of Responsibility
Mark D. McDonnell, Derek Abbott, and Charles E. Pearce
Conference Name
BioMEMS and Nanotechnology (1st : 2003 : Perth, Australia)
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.
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© 2004 COPYRIGHT SPIE--The International Society for Optical Engineering.