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Extending stochastic resonance for neuron models to general Lévy noise.

作者信息

Applebaum David

机构信息

Probability and Statistics Department, University of Sheffield, Sheffield, UK.

出版信息

IEEE Trans Neural Netw. 2009 Dec;20(12):1993-5. doi: 10.1109/TNN.2009.2033183. Epub 2009 Oct 9.

Abstract

A recent paper by Patel and Kosko (2008) demonstrated stochastic resonance (SR) for general feedback continuous and spiking neuron models using additive Lévy noise constrained to have finite second moments. In this brief, we drop this constraint and show that their result extends to general LEvy noise models. We achieve this by showing that "large jump" discontinuities in the noise can be controlled so as to allow the stochastic model to tend to a deterministic one as the noise dissipates to zero. SR then follows by a "forbidden intervals" theorem as in Patel and Kosko's paper.

摘要

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