- Tytuł:
- Stability and dissipativity analysis for neutral type stochastic Markovian jump static neural networks with time delays
- Autorzy:
-
Cao, Yang
Samidurai, R.
Sriraman, R. - Powiązania:
- https://bibliotekanauki.pl/articles/91527.pdf
- Data publikacji:
- 2019
- Wydawca:
- Społeczna Akademia Nauk w Łodzi. Polskie Towarzystwo Sieci Neuronowych
- Tematy:
-
static neural networks
dissipativity analysis
Markovian jump
time-varying delays - Opis:
- 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 toolbox. Finally, examples and simulations are given to show the validity and advantages of the proposed results.
- Źródło:
-
Journal of Artificial Intelligence and Soft Computing Research; 2019, 9, 3; 189-204
2083-2567
2449-6499 - Pojawia się w:
- Journal of Artificial Intelligence and Soft Computing Research
- Dostawca treści:
- Biblioteka Nauki
Artykuł