Global exponential stability of fuzzy logical BAM neural networks with Markovian jumping parameters
Zhengfeng Zhang, Wuneng Zhou, Dongyi Yang · 2011
In this paper, the global exponential stability of fuzzy logical bidirectional associative memory (BAM) neural networks with Markovian jumping parameters is investigated. The jumping parameters considered here are generated from a continuous-time discrete-state homogeneous Markov process and governed by a Markov process with discrete and finite-state space. The purpose of the problem addressed is to derive some new sufficient conditions to ensure the global exponential stability of the fuzzy logical BAM neural networks with Markovian jumping parameters. By employing a new Lyapunov-Krasovshkii functional, a linear matrix inequality (LMI) approach is developed to establish the desired sufficient conditions. Finally a numerical example is provided to demonstrate the effectiveness of the proposed results.