This paper is concerned with the problem of enhanced results on robust finite-time passivity for uncertain discrete-time Markovian jumping BAM delayed neural networks with leakage delay. By implementing a proper Lyapunov-Krasovskii functional candidate, the reciprocally convex combination method together with linear matrix inequality technique, several sufficient conditions are derived for varying the passivity of discrete-time BAM neural networks. An important feature presented in our paper is that we utilize the reciprocally convex combination lemma in the main section and the relevance of that lemma arises from the derivation of stability by using Jensen's inequality. Further, the zero inequalities help to propose the sufficient conditions for finite-time boundedness and passivity for uncertainties. Finally, the enhancement of the feasible region of the proposed criteria is shown via numerical examples with simulation to illustrate the applicability and usefulness of the proposed method.

中文翻译：

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具有泄漏延迟的Markovian跳跃离散时间BAM神经网络的增强鲁棒有限时间无源性。

本文关注的是不确定的离散时间马尔可夫跳跃BAM时滞神经网络的鲁棒有限时间无源性提高结果的问题。通过实现适当的Lyapunov-Krasovskii函数候选，双向凸组合方法以及线性矩阵不等式技术，得出了用于改变离散时间BAM神经网络的无源性的几个充分条件。本文提出的一个重要特征是，我们在主体部分利用了互为凸的组合引理，并且该引理的相关性是通过使用詹森不等式推导稳定性而产生的。此外，零不等式有助于为有限时间有界性和不确定性的被动性提供充分的条件。最后，