Abstract and Applied Analysis
- Abstr. Appl. Anal.
- Volume 2014, Special Issue (2013), Article ID 597298, 8 pages.
Finite-Time Boundedness for a Class of Delayed Markovian Jumping Neural Networks with Partly Unknown Transition Probabilities
This paper is concerned with the problem of finite-time boundedness for a class of delayed Markovian jumping neural networks with partly unknown transition probabilities. By introducing the appropriate stochastic Lyapunov-Krasovskii functional and the concept of stochastically finite-time stochastic boundedness for Markovian jumping neural networks, a new method is proposed to guarantee that the state trajectory remains in a bounded region of the state space over a prespecified finite-time interval. Finally, numerical examples are given to illustrate the effectiveness and reduced conservativeness of the proposed results.
Abstr. Appl. Anal., Volume 2014, Special Issue (2013), Article ID 597298, 8 pages.
First available in Project Euclid: 6 October 2014
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Liang, Li. Finite-Time Boundedness for a Class of Delayed Markovian Jumping Neural Networks with Partly Unknown Transition Probabilities. Abstr. Appl. Anal. 2014, Special Issue (2013), Article ID 597298, 8 pages. doi:10.1155/2014/597298. https://projecteuclid.org/euclid.aaa/1412605771