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Abstract and Applied Analysis
Volume 2014 (2014), Article ID 597298, 8 pages
Research Article

Finite-Time Boundedness for a Class of Delayed Markovian Jumping Neural Networks with Partly Unknown Transition Probabilities

College of Information Sciences and Technology, Hainan University, Haikou 570228, China

Received 11 November 2013; Accepted 8 December 2013; Published 6 January 2014

Academic Editor: Zhengguang Wu

Copyright © 2014 Li Liang. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


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.