Journal
JOURNAL OF ARTIFICIAL INTELLIGENCE AND SOFT COMPUTING RESEARCH
Volume 9, Issue 3, Pages 189-204Publisher
SCIENDO
DOI: 10.2478/jaiscr-2019-0003
Keywords
Static neural networks; Dissipativity analysis; Markovian jump; Time-varying delays
Categories
Ask authors/readers for more resources
This paper studies the global asymptotic stability and dissipativity problem for a class of neutral type stochastic Markovian Jump Static Neural Networks (NTSMJSNNs) with time-varying delays. By constructing an appropriate Lyapunov-Krasovskii Functional (LKF) with some augmented delay-dependent terms and by using integral inequalities to bound the derivative of the integral terms, some new sufficient conditions have been obtained, which ensure that the global asymptotic stability in the mean square. The results obtained in this paper are expressed in terms of Strict Linear Matrix Inequalities (LMIs), whose feasible solutions can be verified by effective MATLAB LMI control tool-box. Finally, examples and simulations are given to show the validity and advantages of the proposed results.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available