Fixed-time synchronization of Inertial Cohen-Grossberg Neural Networks with state dependent delayed impulse control and its application to multi-image encryption

P. Kowsalya, S.S. Mohanrasu, Ardak Kashkynbayev, P. Gokul and R. Rakkiyappan

Chaos, Solitons & Fractals, 2024, vol. 181, issue C

Abstract: In this paper, we discussed about fixed-time synchronization (FXTS) of Inertial Cohen-Grossberg Neural Networks (ICGNNs) with state-dependent delayed impulses. The Lyapunov stability theory and several useful criteria are utilized to make sure that the control parameters are selected in sync with the intended settling time. Two types of the controller are developed in order to guarantee that error-delayed ICGNNs can be synchronized. A sufficient condition for ensuring FXTS for delayed ICGNNs with desynchronization impulses is investigated. In FXTS, the settling time of ICGNNs will have the smallest upper bound and the settling time of desynchronization will have the largest upper bound. We subsequently conducted numerical simulations to substantiate the validity of the proposed discoveries. Finally, we proposed a multi-image encryption algorithm with the help of ICGNNs and presented the statistical analysis to test its efficacy.

Keywords: Inertial Cohen-Grossberg Neural Networks; Fixed-time stability; Settling time; Impulsive control; Fixed-time synchronization; Multi-image encryption (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:chsofr:v:181:y:2024:i:c:s0960077924002455

DOI: 10.1016/j.chaos.2024.114693

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