Title :
Stochastic Exponential Stability for Markovian Jumping BAM Neural Networks With Time-Varying Delays
Author :
Lou, Xuyang ; Cui, Baotong
Author_Institution :
Res. Center of Control Sci. & Eng., Southern Yangtze Univ., Wuxi
fDate :
6/1/2007 12:00:00 AM
Abstract :
This correspondence provides stochastic exponential stability for Markovian jumping bidirectional associative memory neural networks with time-varying delays. An approach combining the Lyapunov functional with linear matrix inequality is taken to study the problems. Some criteria for the stochastic exponential stability are derived. The results obtained in this correspondence are less conservative, less restrictive, and more computationally efficient than the ones reported so far in the literature
Keywords :
Lyapunov methods; Markov processes; asymptotic stability; content-addressable storage; delays; linear matrix inequalities; neural nets; Lyapunov function; Markovian jumping bidirectional associative memory neural networks; linear matrix inequality; stochastic exponential stability; time-varying delays; Associative memory; Delay; Differential equations; Linear matrix inequalities; Magnesium compounds; Neural networks; Pattern recognition; Stability criteria; Stochastic processes; Symmetric matrices; Bidirectional associative memory (BAM); Markovian jumping parameters; linear matrix inequality (LMI); stochastic exponential stability; time-varying delays; Algorithms; Computer Simulation; Markov Chains; Models, Statistical; Neural Networks (Computer); Nonlinear Dynamics; Pattern Recognition, Automated; Stochastic Processes;
Journal_Title :
Systems, Man, and Cybernetics, Part B: Cybernetics, IEEE Transactions on
DOI :
10.1109/TSMCB.2006.887426
