IEICE TRANSACTIONS on Fundamentals
Influence of Additive and Contaminant Noise on Control-Feedback Induced Chaotic Resonance in Excitatory-Inhibitory Neural Systems
Summary :
Recent developments in engineering applications of stochastic resonance have expanded to various fields, especially biomedicine. Deterministic chaos generates a phenomenon known as chaotic resonance, which is similar to stochastic resonance. However, engineering applications of chaotic resonance are limited owing to the problems in controlling chaos, despite its uniquely high sensitivity to weak signal responses. To tackle these problems, a previous study proposed “reduced region of orbit” (RRO) feedback methods, which cause chaotic resonance using external feedback signals. However, this evaluation was conducted under noise-free conditions. In actual environments, background noise and measurement errors are inevitable in the estimation of RRO feedback strength; therefore, their impact must be elucidated for the application of RRO feedback methods. In this study, we evaluated the chaotic resonance induced by the RRO feedback method in chaotic neural systems in the presence of stochastic noise. Specifically, we focused on the chaotic resonance induced by RRO feedback signals in a neural system composed of excitatory and inhibitory neurons, a typical neural system wherein chaotic resonance is observed in the presence of additive noise and feedback signals including the measurement error (called contaminant noise). It was found that for a relatively small noise strength, both types of noise commonly degenerated the degree of synchronization in chaotic resonance induced by RRO feedback signals, although these characteristics were significantly different. In contrast, chaos-chaos intermittency synchronization was observed for a relatively high noise strength owing to the noise-induced attractor merging bifurcation for both types of noise. In practical neural systems, the influence of noise is unavoidable; therefore, this study highlighted the importance of the countermeasures for noise in the application of chaotic resonance and utilization of noise-induced attractor merging bifurcation.
- Publication
- IEICE TRANSACTIONS on Fundamentals Vol.E106-A No.1 pp.11-22
- Publication Date
- 2023/01/01
- Publicized
- 2022/07/07
- Online ISSN
- 1745-1337
- DOI
- 10.1587/transfun.2022EAP1024
- Type of Manuscript
- PAPER
- Category
- Nonlinear Problems
Authors
Sou NOBUKAWA
Department of Computer Science, Chiba Institute of Technology,National Center of Neurology and Psychiatry
Nobuhiko WAGATSUMA
Toho University
Haruhiko NISHIMURA
University of Hyogo
Keiichiro INAGAKI
Chubu University
Teruya YAMANISHI
Osaka Seikei University
Keyword
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Sou NOBUKAWA, Nobuhiko WAGATSUMA, Haruhiko NISHIMURA, Keiichiro INAGAKI, Teruya YAMANISHI, "Influence of Additive and Contaminant Noise on Control-Feedback Induced Chaotic Resonance in Excitatory-Inhibitory Neural Systems" in IEICE TRANSACTIONS on Fundamentals,
vol. E106-A, no. 1, pp. 11-22, January 2023, doi: 10.1587/transfun.2022EAP1024.
Abstract: Recent developments in engineering applications of stochastic resonance have expanded to various fields, especially biomedicine. Deterministic chaos generates a phenomenon known as chaotic resonance, which is similar to stochastic resonance. However, engineering applications of chaotic resonance are limited owing to the problems in controlling chaos, despite its uniquely high sensitivity to weak signal responses. To tackle these problems, a previous study proposed “reduced region of orbit” (RRO) feedback methods, which cause chaotic resonance using external feedback signals. However, this evaluation was conducted under noise-free conditions. In actual environments, background noise and measurement errors are inevitable in the estimation of RRO feedback strength; therefore, their impact must be elucidated for the application of RRO feedback methods. In this study, we evaluated the chaotic resonance induced by the RRO feedback method in chaotic neural systems in the presence of stochastic noise. Specifically, we focused on the chaotic resonance induced by RRO feedback signals in a neural system composed of excitatory and inhibitory neurons, a typical neural system wherein chaotic resonance is observed in the presence of additive noise and feedback signals including the measurement error (called contaminant noise). It was found that for a relatively small noise strength, both types of noise commonly degenerated the degree of synchronization in chaotic resonance induced by RRO feedback signals, although these characteristics were significantly different. In contrast, chaos-chaos intermittency synchronization was observed for a relatively high noise strength owing to the noise-induced attractor merging bifurcation for both types of noise. In practical neural systems, the influence of noise is unavoidable; therefore, this study highlighted the importance of the countermeasures for noise in the application of chaotic resonance and utilization of noise-induced attractor merging bifurcation.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/transfun.2022EAP1024/_p
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@ARTICLE{e106-a_1_11,
author={Sou NOBUKAWA, Nobuhiko WAGATSUMA, Haruhiko NISHIMURA, Keiichiro INAGAKI, Teruya YAMANISHI, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Influence of Additive and Contaminant Noise on Control-Feedback Induced Chaotic Resonance in Excitatory-Inhibitory Neural Systems},
year={2023},
volume={E106-A},
number={1},
pages={11-22},
abstract={Recent developments in engineering applications of stochastic resonance have expanded to various fields, especially biomedicine. Deterministic chaos generates a phenomenon known as chaotic resonance, which is similar to stochastic resonance. However, engineering applications of chaotic resonance are limited owing to the problems in controlling chaos, despite its uniquely high sensitivity to weak signal responses. To tackle these problems, a previous study proposed “reduced region of orbit” (RRO) feedback methods, which cause chaotic resonance using external feedback signals. However, this evaluation was conducted under noise-free conditions. In actual environments, background noise and measurement errors are inevitable in the estimation of RRO feedback strength; therefore, their impact must be elucidated for the application of RRO feedback methods. In this study, we evaluated the chaotic resonance induced by the RRO feedback method in chaotic neural systems in the presence of stochastic noise. Specifically, we focused on the chaotic resonance induced by RRO feedback signals in a neural system composed of excitatory and inhibitory neurons, a typical neural system wherein chaotic resonance is observed in the presence of additive noise and feedback signals including the measurement error (called contaminant noise). It was found that for a relatively small noise strength, both types of noise commonly degenerated the degree of synchronization in chaotic resonance induced by RRO feedback signals, although these characteristics were significantly different. In contrast, chaos-chaos intermittency synchronization was observed for a relatively high noise strength owing to the noise-induced attractor merging bifurcation for both types of noise. In practical neural systems, the influence of noise is unavoidable; therefore, this study highlighted the importance of the countermeasures for noise in the application of chaotic resonance and utilization of noise-induced attractor merging bifurcation.},
keywords={},
doi={10.1587/transfun.2022EAP1024},
ISSN={1745-1337},
month={January},}
Copy
TY - JOUR
TI - Influence of Additive and Contaminant Noise on Control-Feedback Induced Chaotic Resonance in Excitatory-Inhibitory Neural Systems
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 11
EP - 22
AU - Sou NOBUKAWA
AU - Nobuhiko WAGATSUMA
AU - Haruhiko NISHIMURA
AU - Keiichiro INAGAKI
AU - Teruya YAMANISHI
PY - 2023
DO - 10.1587/transfun.2022EAP1024
JO - IEICE TRANSACTIONS on Fundamentals
SN - 1745-1337
VL - E106-A
IS - 1
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - January 2023
AB - Recent developments in engineering applications of stochastic resonance have expanded to various fields, especially biomedicine. Deterministic chaos generates a phenomenon known as chaotic resonance, which is similar to stochastic resonance. However, engineering applications of chaotic resonance are limited owing to the problems in controlling chaos, despite its uniquely high sensitivity to weak signal responses. To tackle these problems, a previous study proposed “reduced region of orbit” (RRO) feedback methods, which cause chaotic resonance using external feedback signals. However, this evaluation was conducted under noise-free conditions. In actual environments, background noise and measurement errors are inevitable in the estimation of RRO feedback strength; therefore, their impact must be elucidated for the application of RRO feedback methods. In this study, we evaluated the chaotic resonance induced by the RRO feedback method in chaotic neural systems in the presence of stochastic noise. Specifically, we focused on the chaotic resonance induced by RRO feedback signals in a neural system composed of excitatory and inhibitory neurons, a typical neural system wherein chaotic resonance is observed in the presence of additive noise and feedback signals including the measurement error (called contaminant noise). It was found that for a relatively small noise strength, both types of noise commonly degenerated the degree of synchronization in chaotic resonance induced by RRO feedback signals, although these characteristics were significantly different. In contrast, chaos-chaos intermittency synchronization was observed for a relatively high noise strength owing to the noise-induced attractor merging bifurcation for both types of noise. In practical neural systems, the influence of noise is unavoidable; therefore, this study highlighted the importance of the countermeasures for noise in the application of chaotic resonance and utilization of noise-induced attractor merging bifurcation.
ER -
English
