Abstract
This article explores the \({\cal O}({t^{ - \beta }})\) synchronization and asymptotic synchronization for fractional order BAM neural networks (FBAMNNs) with discrete delays, distributed delays and non-identical perturbations. By designing a state feedback control law and a new kind of fractional order Lyapunov functional, a new set of algebraic sufficient conditions are derived to guarantee the \({\cal O}({t^{ - \beta }})\) Synchronization and asymptotic synchronization of the considered FBAMNNs model; this can easily be evaluated without using a MATLAB LMI control toolbox. Finally, two numerical examples, along with the simulation results, illustrate the correctness and viability of the exhibited synchronization results.
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This article has been written with the joint financial support of Thailand Research Fund RSA 6280004, RUSA-Phase 2.0 Grant No.F 24-51/2014-U, Policy (TN Multi-Gen), Dept. of Edn. Govt. of India, UGC-SAP (DRS-I) Grant No.F.510/8/DRS-I/2016(SAP-I), DST (FIST — level I) 657876570 Grant No.SR/FIST/MS-I/2018/17 and Prince Sultan University for funding this work through research group Nonlinear Analysis Methods in Applied Mathematics (NAMAM) group number RG-DES-2017-01-17.
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Pratap, A., Raja, R., Cao, J. et al. \({\cal O}({t^{ - \beta }})\)-Synchronization and Asymptotic Synchronization of Delayed Fractional Order Neural Networks. Acta Math Sci 42, 1273–1292 (2022). https://doi.org/10.1007/s10473-022-0402-7
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DOI: https://doi.org/10.1007/s10473-022-0402-7
Key words
- \({\cal O}({{\bf{t}}^{ - \beta }})\)-synchronization
- asymptotic synchronization
- BAM neural networks
- fractional order
- state feedback control law