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The stationarity control of the average links for the Hebb complex dynamical network via external stimulus signals.
Peng, Yi; Wang, Yinhe; Gao, Peitao; Zhang, Lili.
Afiliación
  • Peng Y; School of Automation, Guangdong University of Technology, Guangzhou, Guangdong 510006, PR China.
  • Wang Y; School of Automation, Guangdong University of Technology, Guangzhou, Guangdong 510006, PR China.
  • Gao P; School of Automation, Guangdong University of Technology, Guangzhou, Guangdong 510006, PR China. Electronic address: peitao_gao@sina.com.
  • Zhang L; School of Mathematics and Statistics, Guangdong University of Technology, Guangzhou, Guangdong 510006, PR China.
ISA Trans ; 132: 338-345, 2023 Jan.
Article en En | MEDLINE | ID: mdl-35725668
ABSTRACT
The model of complex dynamical network (CDN) can be represented as the mathematic graph, in which some characteristics may emerge from the dynamic nodes group (NG) and links group (LG). This paper primarily focuses on the feature appearing from the dynamic links. The average link weight (ALW), as a novel quantitative index to describe the characteristic of dynamic links is introduced. Inspired by the Hebb's neuroscience theory, the Hebb complex dynamical network (HCDN) is constructed. The ALW of the HCDN can track a given target via external stimulus signals with adaptive amplifiers' proportional coefficients. In other words, the stationary network implies the ALW is a constant in time. Finally, two simulation examples are performed to validate the proposed adaptive update law's effectiveness.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: ISA Trans Año: 2023 Tipo del documento: Article

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: ISA Trans Año: 2023 Tipo del documento: Article