$$H_\infty $$ State Estimation for Round-Robin Protocol-Based Markovian Jumping Neural Networks with Mixed Time Delays

This paper discusses the $$H_\infty $$ state estimation issue in regard to Markovian jumping neural networks (MJNNs) under scheduling of Round-Robin protocol (RRP). The model takes into account mixed time-delays, sensor nonlinearities and exogenous disturbances, making it relatively general comprehensive. transmission MJNNs signals invoked a communication scheme which RRP is used for data transmissions order avoid undesirable collisions. Protocol-dependent estimator modeling hybrid switching system with time delays disturbances designed first achieve asymptotic tracing neuron state. Using Lyapunov stability theory several methods, sufficient conditions guaranteeing are established constraint performance. By employing combination matrix analysis techniques, gain matrices calculated by feasible solutions linear inequalities (LMIs). Finally, numerical example related simulations demonstrate validity proposed model.