Further Results on Dissipativity Criterion for Markovian Jump Discrete-Time Neural Networks with Two Delay Components Via Discrete Wirtinger Inequality Approach
 作者： S. Ramasamy,  G. Nagamani,  T. Radhika 作者单位： 1Gandhigram Rural Institute - Deemed University 刊名： Neural Processing Letters, 2017, Vol.45 (3), pp.939-965 来源数据库： Springer Nature Journal DOI： 10.1007/s11063-016-9559-1 关键词： Additive delay components;  Dissipativity;  Lyapunov–Krasovskii functional;  Linear matrix inequality;  Neural networks; 英文摘要： This paper is concerned with strict $$(\mathcal {Q}, \mathcal {S}, \mathcal {R})-\gamma$$ - dissipativity and passivity analysis for discrete-time Markovian jump neural networks involving both leakage and discrete delays expressed in terms of two additive time-varying delay components. The discretized Wirtinger inequality is utilized to bound the forward difference of finite-sum term in the Lyapunov functional. By constructing a suitable Lyapunov–Krasovskii functional, sufficient conditions are derived to guarantee the dissipativity and passivity criteria of the proposed neural networks. These conditions are presented in terms of linear matrix inequalities (LMIs), which can be efficiently solved via LMI MATLAB Toolbox. Finally, numerical examples are given to illustrate the effectiveness... of the proposed results. 原始语种摘要： This paper is concerned with strict $$(\mathcal {Q}, \mathcal {S}, \mathcal {R})-\gamma$$ - dissipativity and passivity analysis for discrete-time Markovian jump neural networks involving both leakage and discrete delays expressed in terms of two additive time-varying delay components. The discretized Wirtinger inequality is utilized to bound the forward difference of finite-sum term in the Lyapunov functional. By constructing a suitable Lyapunov–Krasovskii functional, sufficient conditions are derived to guarantee the dissipativity and passivity criteria of the proposed neural networks. These conditions are presented in terms of linear matrix inequalities (LMIs), which can be efficiently solved via LMI MATLAB Toolbox. Finally, numerical examples are given to illustrate the effectiveness... of the proposed results.

• Markovian　马尔可夫链的
• passivity　钝态
• delay　延时
• dissipativity　耗散度
• inequality　不等式
• varying　变化的
• components　零部件
• functional　功能的
• effectiveness　有效性
• guarantee　担保