Robust exponential stability for discrete-time interval BAM neural networks with delays and Markovian jump parameters

This paper investigates the problem of global robust exponential stability for discrete-time interval BAM neural networks with mode-dependent time delays and Markovian jump parameters, by utilizing the Lyapunov-Krasovskii functional combined with the linear matrix inequality (LMI) approach. A new Markov process as discrete-time, discrete-state Markov process is considered. An exponential stability performance analysis result is first established for error systems without ignoring any terms in the derivative of Lyapunov functional by considering the relationship between the time-varying delay and its upper bound. The delay factor depends on the mode of operation. Three numerical examples are given to demonstrate the merits of the proposed method.