Robust stability criteria for discrete-time neural networks with mode-dependent time delays and Markovian jump parameters

In this paper, we investigate the time-delay dependent robust stability problem for discrete-time neural networks with mode-dependent time delays. The jumping parameters are considered as discrete-time, discrete-state Markov process. The delay factor depends on the mode of operation. The linear factional uncertainty is considered, which means that less conservative results is obtained than using norm-bounded parameter uncertainties. All the results are cast into convenient linear matrix inequality (LMIs) forms. A numerical example is given to illustrate the effectiveness of the results.