Novel Results on Global Asymptotic Stability of Time-Delayed Complex Valued Bidirectional Associative Memory Neural Networks
N. Mohamed Thoiyab, Saravanan Shanmugam, Rajarathinam Vadivel, Nallappan Gunasekaran · Symmetry · 2025
This study investigates the global asymptotic stability of hybrid bidirectional associative memory (BAM) complex-valued neural networks (CVNNs) with time-varying delays and uncertain parameters, where the system matrices are assumed to be symmetric. By constructing an appropriate Lyapunov–Krasovskii functional (LKF), new sufficient conditions are derived to guarantee the existence and uniqueness of equilibrium points, as well as to establish the global asymptotic stability of the proposed symmetric hybrid BAM CVNNs. The validity and effectiveness of the theoretical results are further demonstrated through detailed numerical examples.