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<p>This study investigates the global Mittag-Leffler stability and synchronization of discrete-time fractional-order complex-valued bidirectional associative memory neural networks (DCVBAMNNs) with time delays. Utilizing fractional calculus in discrete time, the analysis is conducted directly on the complex-valued system without decomposing it into real and imaginary components. Sufficient conditions for the existence and uniqueness of equilibrium points are established using the Laplace transform, discrete fractional analysis, and Mittag-Leffler functions. Furthermore, the fractional Lyapunov method is employed to derive stability and synchronization criteria within the drive-response framework. Theoretical findings are validated through numerical simulations, highlighting their practical significance for complex-valued fractional-order systems.</p>

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Global Mittag-Leffler stability and synchronization of discrete-time fractional-order complex-valued BAM neural networks with time delay

  • 期刊论文

  • 发表日期：

    2025年6月24日

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  • R. Samidurai,
  • M. Yazhini

摘要

This study investigates the global Mittag-Leffler stability and synchronization of discrete-time fractional-order complex-valued bidirectional associative memory neural networks (DCVBAMNNs) with time delays. Utilizing fractional calculus in discrete time, the analysis is conducted directly on the complex-valued system without decomposing it into real and imaginary components. Sufficient conditions for the existence and uniqueness of equilibrium points are established using the Laplace transform, discrete fractional analysis, and Mittag-Leffler functions. Furthermore, the fractional Lyapunov method is employed to derive stability and synchronization criteria within the drive-response framework. Theoretical findings are validated through numerical simulations, highlighting their practical significance for complex-valued fractional-order systems.