Adaptation Using Local Information for Maximizing the Global Cost

Science Direct Working Paper No S1574-034X(04)70425-1

9 Pages Posted: 20 Feb 2018

See all articles by Thomas Hoch

Thomas Hoch

Technische Universität Berlin (TU Berlin)

Gregor Wenning

Technische Universität Berlin (TU Berlin)

Klaus Obermayer

Technische Universität Berlin (TU Berlin)

Date Written: February 2002

Abstract

Recently the information transmission properties of noisy, parallel summing threshold arrays, have been investigated and interpreted in a neural coding context (see Stocks, [1] [2]). The mutual information between certain stimuli and corresponding responses displays a maximum as a function of the noise level. This optimal noise level depends on the number of neurons within the array, information that is not locally available for single neuron adaptation. We give an analytic expression for the optimal noise level, that only depends on locally available information. The result is based upon an approximation to the mutual information. In the large limit both descriptions coincide.

Keywords: Stochastic Resonance, Adaptation, Summing threshold array

Suggested Citation

Hoch, Thomas and Wenning, Gregor and Obermayer, Klaus, Adaptation Using Local Information for Maximizing the Global Cost (February 2002). Computer Science Preprint Archive Vol. 2002, Issue 2, pp 344-352. Available at SSRN: https://ssrn.com/abstract=3117430

Thomas Hoch (Contact Author)

Technische Universität Berlin (TU Berlin)

Straße des 17
Juni 135
Berlin, 10623
Germany

Gregor Wenning

Technische Universität Berlin (TU Berlin)

Straße des 17
Juni 135
Berlin, 10623
Germany

Klaus Obermayer

Technische Universität Berlin (TU Berlin) ( email )

Straße des 17
Juni 135
Berlin, 10623
Germany

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