Improved Stability Criteria of Static Recurrent Neural Networks with a Time-Varying Delay

This paper investigates the stability of static recurrent neural networks (SRNNs) with a time-varying delay. Based on the complete delay-decomposing approach and quadratic separation framework, a novel Lyapunov-Krasovskii functional is constructed. By employing a reciprocally convex technique to con...

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Detalles Bibliográficos
Autores principales: Ding, Lei, Zeng, Hong-Bing, Wang, Wei, Yu, Fei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi Publishing Corporation 2014
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3988971/
https://www.ncbi.nlm.nih.gov/pubmed/25143974
http://dx.doi.org/10.1155/2014/391282

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3988971/
https://www.ncbi.nlm.nih.gov/pubmed/25143974
http://dx.doi.org/10.1155/2014/391282

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