Reconstruction of Chaotic Dynamics via a Network of Stochastic Resonance Neurons and Its Application to Speech

概要

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As a new framework for understanding sensory mechanism of biological systems, a great deal of attention has been recently paid to stochastic resonance. The stochastic resonance explains properties of sensory neurons that accurately detect weak input stimuli by using a small amount of internal noise. In particular, Collins et al. reported that a network of stochastic resonance neurons gives rise to robust sensory function for detecting a variety of complex input signals. In this study, we investigate effectiveness of such stochastic resonance neural networks to chaotic input signals. By using the Rossler equations, we analyze the network capability of detecting chaotic dynamics. We also apply the stochastic resonance network systems to speech signals and examine plausibility of the stochastic resonance neural network as a possible model for the human auditory system.
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