Fractional derivative of Hermite fractal splines on the fractional-order delayed neural networks synchronization

S. S. Mohanrasu, T. M.C. Priyanka, A. Gowrisankar, Ardak Kashkynbayev, K. Udhayakumar, R. Rakkiyappan

Research output: Contribution to journalArticlepeer-review

Abstract

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.

Original languageEnglish
Article number108399
JournalCommunications in Nonlinear Science and Numerical Simulation
Volume140
DOIs
Publication statusPublished - Jan 2025

Keywords

  • Caputo-fractional derivative
  • Hermite fractal interpolation function
  • Intermittent control
  • Synchronization of neural networks

ASJC Scopus subject areas

  • Numerical Analysis
  • Modelling and Simulation
  • Applied Mathematics

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