Dynamics analysis of impulsive stochastic high-order BAM neural networks with Markovian jumping and mixed delays. (English) Zbl 1297.92009
Summary: This paper deals with the problem of asymptotical stability in mean square for a class of impulsive stochastic high-order bi-directional associative memory (BAM) neural networks with mixed delays and Markovian jumping parameters. Based on Lyapunov stability theory, linear matrix inequality and mathematical induction, some sufficient conditions are derived for the asymptotical stability in mean square of the equilibrium point of the neural networks. The results obtained in this paper are new and complement previously known results.
MSC:
| 92B20 | Neural networks for/in biological studies, artificial life and related topics |
| 60H10 | Stochastic ordinary differential equations (aspects of stochastic analysis) |
| 60J28 | Applications of continuous-time Markov processes on discrete state spaces |
Keywords:
high-order BAM neural networks; impulsive; Markovian jumping; mean square asymptotical stabilityReferences:
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