Evaluation of Ability of Chaotic Resonance under Noises in Neural Systems Comprising Excitatory–Inhibitory Neurons

Abstract

Recent studies on stochastic resonance have been considered in various fields for engineering applications. Chaotic dynamics derive a phenomenon called chaotic resonance, which is similar to stochastic resonance. The engineering applications of chaotic resonance are limited due to its controlling difficulty, although it exhibits a high sensitivity to signal responses. To address this limitation, we previously proposed a "reduced region of orbit" (RRO) feedback method which induces chaotic resonance using external feedback signals. This method was evaluated under noise-free conditions. However, in practical scenarios, background noise and measurement error are observed when estimating the RRO feedback strength. The influence of these factors on chaotic resonance must be evaluated for preliminary practical application of chaotic resonance. Therefore, in this study, we evaluated chaotic resonance induced by the RRO feedback method in chaotic neural systems under stochastic noise. We focus on chaotic resonance induced by RRO feedback signals in a discrete neural system comprising excitatory and inhibitory neurons, which are typical neural systems that entail chaotic resonance under additive noise and feedback signals, including measurement errors (called contaminant noise). Although both types of noise commonly degrade the degree of synchronization of chaotic resonance induced by the RRO feedback strength, their characteristics are considerably different. In actual neural systems, the influence of noise is inevitable; therefore, this study highlighted the importance of noise countermeasures during the application of chaotic resonance.