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    Weighted Pseudo Almost-Automorphic Solutions of Quaternion-Valued Rnns With Mixed Delays
    (Springer, 2023) Yazgan, Ramazan; Hajjaji, Salsabil; Cherif, Farouk
    This work deals with a nonlinear differential equation for a quaternion-valued recurrent neural network. By using the contraction mapping principle and some differential inequalities, we directly studied the existence and the global exponential stability of weighted pseudo-almost automorphic solution for this class of quaternion-valued neural networks. Here, methods were applied without a real or a complex decomposition of the equation system. In addition, an application verifying our results and its numerical simulation was given. The generated results about the weighted pseudo-almost automorphic solution of the considered model are new.