The issue of synchronization for a class of inertial memristive neural networks over a finite-time interval is investigated in this paper. Specifically, reaction-diffusion items and Markovian jump parameters are both considered in the system model, meanwhile, a novel nonfragile time-varying proportional retarded control strategy is proposed. First, a befitting variable substitution is invoked to transform the original second-order differential system into a first-order one so that the corresponding synchronization error system that is represented by a first-order differential form is established. Second, by utilizing the integral inequality technique, reciprocally convex combination approach and free-weighting matrix method, a less conservative synchronization criterion in terms of linear matrix inequalities is obtained. Finally, three simulations are exploited to illustrate the feasibility, practicability and superiority of the designed controller so that the acquired theoretical results are supported.

中文翻译：

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具有反应扩散项的马尔可夫惯性忆阻神经网络的有限时间非脆弱时变比例延迟同步。

研究了一类惯性忆阻神经网络在有限时间间隔内的同步问题。具体地，在系统模型中考虑了反应扩散项和马尔可夫跳跃参数，同时提出了一种新颖的非脆弱时变比例滞后控制策略。首先，调用合适的变量替换以将原始的二阶微分系统转换为一阶微分系统，从而建立由一阶微分形式表示的相应同步误差系统。其次，利用积分不等式技术，双向凸组合法和自由加权矩阵法，获得了线性矩阵不等式不那么保守的同步准则。最后，