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Adaptation using Local Information for Maximizing the Global Cost
Citation key Hochreiter2003a
Author Hoch, T. and Wenning, G. and Obermayer, K.
Pages 467-472
Year 2003
DOI 10.1016/S0925-2312(02)00779-8
Journal Neurocomputing
Volume 52 – 54
Publisher Elsevier
Abstract Recently the information transmission properties of noisy, parallel summing threshold arrays, have been investigated and interpreted in a neural coding context (see Stocks, Phys. Rev. Lett. 84 (2000) 2310; Phys. Rev. E 63 (2001) 1). 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 N 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 N limit both descriptions coincide.
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