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Robust Nonlinear Dynamics Conditions That Arise in Self-oscillatory Networks
https://ipsj.ixsq.nii.ac.jp/records/241913
https://ipsj.ixsq.nii.ac.jp/records/241913bf78d3df-816d-423a-9bc5-086c391401a6
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2027年1月14日からダウンロード可能です。
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Copyright (c) 2025 by the Information Processing Society of Japan
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非会員:¥0, IPSJ:学会員:¥0, 論文誌:会員:¥0, DLIB:会員:¥0 |
Item type | Journal(1) | |||||||||
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公開日 | 2025-01-15 | |||||||||
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タイトル | Robust Nonlinear Dynamics Conditions That Arise in Self-oscillatory Networks | |||||||||
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言語 | en | |||||||||
タイトル | Robust Nonlinear Dynamics Conditions That Arise in Self-oscillatory Networks | |||||||||
言語 | ||||||||||
言語 | eng | |||||||||
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主題Scheme | Other | |||||||||
主題 | [一般論文] self-oscillatory networks, limit cycles, central pattern generators, dynamical systems | |||||||||
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資源タイプ識別子 | http://purl.org/coar/resource_type/c_6501 | |||||||||
資源タイプ | journal article | |||||||||
著者所属 | ||||||||||
値 | Kyushu University | |||||||||
著者所属 | ||||||||||
値 | Kyushu University/The University of Tokyo | |||||||||
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言語 | en | |||||||||
値 | Kyushu University | |||||||||
著者所属(英) | ||||||||||
言語 | en | |||||||||
値 | Kyushu University / The University of Tokyo | |||||||||
著者名 |
Tham, Yik Foong
× Tham, Yik Foong
× Danilo, Vasconcellos Vargas
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著者名(英) |
Tham, Yik Foong
× Tham, Yik Foong
× Danilo, Vasconcellos Vargas
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論文抄録 | ||||||||||
内容記述タイプ | Other | |||||||||
内容記述 | Self-oscillation is an emergent behavior naturally occurring in biological neural circuits, facilitating the coordination of complex locomotion and cognitive functions. Recently, numerous discrete dynamical system models, termed Self-Oscillatory Networks (SONs), have been proposed to model the functional behavior of such neural circuits. In brief, SONs are recurrent neural networks that generate spontaneous, self-sustaining rhythmic patterns without any input. However, the internal dynamics of SONs, especially in systems of high dimensionality, remain unexplored due to their complexity. This paper analyzes the robust nonlinear dynamics that arise within SONs. Through numerical analyses, we examine the influence of spectral radius on the emergence of dynamic attractors, particularly limit cycles. Following that, we identify the critical value of the spectral radius that induces a supercritical Hopf bifurcation in the system of SONs. We also perform stability analysis using Lyapunov exponents and phase shift to demonstrate that SONs exhibit robust behavior against perturbations. Therefore, we conclude that SONs contain cyclic attractors that maintain stable limit cycles, even under perturbations. ------------------------------ This is a preprint of an article intended for publication Journal of Information Processing(JIP). This preprint should not be cited. This article should be cited as: Journal of Information Processing Vol.33(2025) (online) DOI http://dx.doi.org/10.2197/ipsjjip.33.21 ------------------------------ |
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論文抄録(英) | ||||||||||
内容記述タイプ | Other | |||||||||
内容記述 | Self-oscillation is an emergent behavior naturally occurring in biological neural circuits, facilitating the coordination of complex locomotion and cognitive functions. Recently, numerous discrete dynamical system models, termed Self-Oscillatory Networks (SONs), have been proposed to model the functional behavior of such neural circuits. In brief, SONs are recurrent neural networks that generate spontaneous, self-sustaining rhythmic patterns without any input. However, the internal dynamics of SONs, especially in systems of high dimensionality, remain unexplored due to their complexity. This paper analyzes the robust nonlinear dynamics that arise within SONs. Through numerical analyses, we examine the influence of spectral radius on the emergence of dynamic attractors, particularly limit cycles. Following that, we identify the critical value of the spectral radius that induces a supercritical Hopf bifurcation in the system of SONs. We also perform stability analysis using Lyapunov exponents and phase shift to demonstrate that SONs exhibit robust behavior against perturbations. Therefore, we conclude that SONs contain cyclic attractors that maintain stable limit cycles, even under perturbations. ------------------------------ This is a preprint of an article intended for publication Journal of Information Processing(JIP). This preprint should not be cited. This article should be cited as: Journal of Information Processing Vol.33(2025) (online) DOI http://dx.doi.org/10.2197/ipsjjip.33.21 ------------------------------ |
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収録物識別子タイプ | NCID | |||||||||
収録物識別子 | AN00116647 | |||||||||
書誌情報 |
情報処理学会論文誌 巻 66, 号 1, 発行日 2025-01-15 |
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収録物識別子タイプ | ISSN | |||||||||
収録物識別子 | 1882-7764 | |||||||||
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言語 | ja | |||||||||
出版者 | 情報処理学会 |