Fractional derivative of Hermite fractal splines on the fractional-order delayed neural networks synchronization
Mohanrasu S.S. Priyanka T.M.C. Gowrisankar A. Kashkynbayev A. Udhayakumar K. Rakkiyappan R.
January 2025Elsevier B.V.
Communications in Nonlinear Science and Numerical Simulation
2025#140
The purpose of this research is twofold. First, the master–slave synchronization of fractional-order neural networks is explored with time delays using aperiodic intermittent control. Then we present a sufficient condition for master–slave synchronization of delayed fractional-order neural networks via average-width intermittent control technique. A numerical simulation is used to demonstrate the efficacy of the derived results. Second, a novel investigation of the Caputo-fractional derivative of Hermite fractal splines is accomplished. Moreover, its box counting dimension is estimated and related with the Caputo-fractional order. Additionally, we propose an image encryption algorithm utilizing the semi-tensor product (STP). The efficiency of the algorithm is evaluated through the application of statistical measures.
Caputo-fractional derivative , Hermite fractal interpolation function , Intermittent control , Synchronization of neural networks
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Department of Mathematics, Bharathiar University, Tamil Nadu, Coimbatore, 641 046, India
Department of Mathematics, School of Advanced Sciences, Vellore Institute of Technology, Tamil Nadu, Vellore, 632 014, India
Department of Mathematics, Nazarbayev University, Nur-Sulthan city, Kazakhstan
Department of Mathematical Sciences, College of Science, UAE University, Al-Ain, United Arab Emirates
Department of Mathematics
Department of Mathematics
Department of Mathematics
Department of Mathematical Sciences
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