Mean-square stability of stochastic quaternion-valued neural networks with variable coefficients and neutral delays

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Abstract

In this paper, the stochastic quaternion-valued neural networks model with variable coefficients and neutral delays is considered, and the mean-square stability criterion is provided via the method of mathematical analysis. In deriving stability criterion, the considered stochastic quaternion-valued neural networks model is implemented as an entirety form without separating the model into two complex-valued or four real-valued models. And the obtained result is valid for stochastic real-valued and complex-valued neural networks. A numerical simulation example is given to show the effectiveness of the obtained result.

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Song, Q., Zeng, R., Zhao, Z., Liu, Y., & Alsaadi, F. E. (2022). Mean-square stability of stochastic quaternion-valued neural networks with variable coefficients and neutral delays. Neurocomputing, 471, 130–138. https://doi.org/10.1016/j.neucom.2021.11.033

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