Reduced-order state estimation of complex-valued neural networks with generally uncertain transition rates Markovian jump

In this work, a reduced-order state estimator is used to estimate the state of the complex-valued neutral networks (CVNNs) while do not divide it into a real component and an imaginary component. On the one hand, new state feedback controllers are designed to stabilize the error system we obtained; On the other hand, a example is given to prove the validity and correctness of our theorem.