数学
区间(图论)
泄漏(经济)
稳定性判据
控制理论(社会学)
理论(学习稳定性)
人工神经网络
上下界
线性矩阵不等式
凸组合
重积分
正多边形
应用数学
凸优化
数学优化
数学分析
计算机科学
离散时间和连续时间
控制(管理)
统计
组合数学
机器学习
宏观经济学
人工智能
经济
几何学
作者
R. Manivannan,Rajendran Samidurai,Jinde Cao,Ahmed Alsaedi,Fuad E. Alsaadi
标识
DOI:10.1186/s13662-018-1509-y
摘要
We examine the stability problem for delayed neutral-type neural networks (NNs) with interval time-varying delay signals under the effects of leakage term by constructing a suitable Lyapunov–Krasovskii functionals (LKFs) with the triple- and four-integral terms and using the famous Jensen inequality, Wirtinger single integral inequality (WSII), and Wirtinger double integral inequality (WDII), combined with the reciprocally convex approach (RCC) for the stability of addressing NNs. Therefore, the major contribution of this study lies in a consideration of new integral inequalities and improved LKFs, fully taking the relationship between the terms in the Leibniz–Newton formula within the framework of linear matrix inequalities (LMIs). Moreover, we assume that the lower bound of interval time-varying delay is not restricted to zero. Using several examples, we show that the proposed stability criterion is less conservative than previous results. Also, the proposed technique is applied to benchmark problem that is associated with reasonable issues to showing feasibility on a real-world problem, including transporting time delay signals and leakage delay as a process variable in the quadruple-tank process system.
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