 Lipschitz stability analysis of fractional-order impulsive delayed reaction-diffusion neural network modelsIvanka Stamova, Trayan Stamov and Gani Stamov Chaos, Solitons & Fractals, 2022, vol. 162, issue C Abstract: In this paper, the concept of Lipschitz stability is introduced to impulsive delayed reaction-diffusion neural network models of fractional order. Such networks are an appropriate modeling tool for studying various problems in engineering, biology, neuroscience and medicine. Fractional derivatives of Caputo type are considered in the model. The effects of impulsive perturbations and delays are also under consideration. Lipschitz stability analysis is performed and sufficient conditions for global uniform Lipschitz stability of the model are established. The Lyapunov function approach combined with the comparison principle are employed in the development of the main results. The proposed criteria extend some existing stability results for such models to the Lipschitz stability case. The introduced concept is also very useful in numerous inverse problems. Keywords: Lipschitz stability; Reaction-diffusion neural networks; Fractional; Delays; Impulses (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:chsofr:v:162:y:2022:i:c:s0960077922006841 DOI: 10.1016/j.chaos.2022.112474 Access Statistics for this article Chaos, Solitons & Fractals is currently edited by Stefano Boccaletti and Stelios Bekiros More articles in Chaos, Solitons & Fractals from Elsevier |
Is your work missing from RePEc? Here is how to contribute.
Questions or problems? Check the EconPapers FAQ or send mail to .
EconPapers is hosted by the
School of Business at Örebro University.