Stability and Spatiotemporal Bifurcations in Spatially Distributed Neural Networks with Nonlocal Delay.
The stability of equilibria and bifurcations of neural networks in a real line with nonlocal delay are presented. A sufficient condition of stable equilibria is declared by the linear part. Eigenvalue analysis implies the existence of bifurcations, and by exploiting typical excitatory and inhibitory...
| Publicado en: | Zeitschrift für Naturforschung Section A: A Journal of Physical Sciences Vol. 73; no. 9; pp. 815 - 824 |
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| Autores principales: | , |
| Formato: | Artículo |
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De Gruyter
Sep2018
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=hlh&AN=131583515&site=ehost-live header: @attributes: shortDbName: hlh uiTerm: 131583515 longDbName: Humanities International Complete uiTag: AN controlInfo: bkinfo: jinfo: jid: 09320784 FL07 jtl: Zeitschrift für Naturforschung Section A: A Journal of Physical Sciences issn: 09320784 maglogo: N pubinfo: dt: Sep2018 vid: 73 iid: 9 pid: 1734 pub: De Gruyter artinfo: ui: 131583515 10.1515/zna-2018-0116 ppf: 815 ppct: 9 formats: tig: atl: Stability and Spatiotemporal Bifurcations in Spatially Distributed Neural Networks with Nonlocal Delay. aug: au: Yanqiu Li Juncheng Jiang affil: School of Physical and Mathematical Sciences, Nanjing University of Technology, Nanjing 211816, China College of Safety Science and Engineering, Nanjing University of Technology, Nanjing 211816, China su: Spatiotemporal processes Bifurcation theory Eigenvalue equations Artificial neural networks Acid-base equilibrium sug: subj: Spatiotemporal processes Bifurcation theory Eigenvalue equations Artificial neural networks Acid-base equilibrium keyword: Bifurcation Neural Network Nonlocal Delay Pattern Formation Spatiotemporal Interaction ab: The stability of equilibria and bifurcations of neural networks in a real line with nonlocal delay are presented. A sufficient condition of stable equilibria is declared by the linear part. Eigenvalue analysis implies the existence of bifurcations, and by exploiting typical excitatory and inhibitory connectivity kernels in a neural network, the possible bifurcations are discussed according to various cases. It is an advantageous tool using a multiple-scale method to study the stability of bifurcated travelling waves or spots. As an illustration of our theory, the dynamics of a seashell continuous-time circular mask model are investigated. It is shown that both the shape and range of active function and synaptic weights can affect the dynamics of the model. Finally, the bifurcation set and the variety of bifurcated patterns of the seashell model are numerically revealed. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: Y dt: @attributes: year: 2018 holdings: @attributes: islocal: N |
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