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Semi-Global Polynomial Synchronization of High-Order Multiple Proportional-Delay BAM Neural Networks

Author

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  • Er-yong Cong

    (Department of Mathematics, Harbin University, Harbin 150086, China
    Heilongjiang Provincial Key Laboratory of the Intelligent Perception and Intelligent Software, Harbin University, Harbin 150080, China)

  • Xian Zhang

    (School of Mathematical Science, Heilongjiang University, Harbin 150080, China
    Heilongjiang Provincial Key Laboratory of the Theory and Computation of Complex Systems, Heilongjiang University, Harbin 150080, China)

  • Li Zhu

    (Department of Mathematics, Harbin University, Harbin 150086, China)

Abstract

This paper addresses the semi-global polynomial synchronization (SGPS) problem for a class of high-order bidirectional associative memory neural networks (HOBAMNNs) with multiple proportional delays. The time-delay-dependent semi-global polynomial stability criterion for error systems was established via a direct approach. The derived stability conditions are formulated as several simple inequalities that are readily solvable, facilitating direct verification using standard computational tools (e.g., YALMIP). Notably, this method can be applied to many system models with proportional delays after minor modifications. Finally, a numerical example is provided to validate the effectiveness of the theoretical results.

Suggested Citation

  • Er-yong Cong & Xian Zhang & Li Zhu, 2025. "Semi-Global Polynomial Synchronization of High-Order Multiple Proportional-Delay BAM Neural Networks," Mathematics, MDPI, vol. 13(9), pages 1-16, May.
    • Handle: RePEc:gam:jmathe:v:13:y:2025:i:9:p:1512-:d:1649124
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