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- W4385574710 abstract "In this article, the global asymptotic stability of a class of recurrent neural networks (RNNs) with generalized piecewise constant argument (GPCA) is investigated. By the Banach fixed point theorem (BFPT) and comparison principle, a set of improved criteria are presented to guarantee the existence and uniqueness (EU) of the solutions and global asymptotic stability of equilibrium point for the considered RNNs. Compared with the existing results, this article not only reduces the requirements for system parameters, but also provides more criteria in different forms, which greatly improve the feasible range of the obtained criteria. The effectiveness of the obtained results are tested by some numerical examples." @default.
- W4385574710 created "2023-08-05" @default.
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- W4385574710 date "2023-11-01" @default.
- W4385574710 modified "2023-10-18" @default.
- W4385574710 title "Improved Criteria for Stability of a Class of Recurrent Neural Networks With Generalized Piecewise Constant Argument" @default.
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- W4385574710 doi "https://doi.org/10.1109/tsmc.2023.3295837" @default.
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