Adaptive estimation for delayed neural networks with Markovian jumping parameters

In this letter, the adaptive estimation problem of the neuron states is studied for delayed neural networks with Markovian jumping parameters. Through employing a new nonnegative function and the M-matrix method, some sufficient conditions are derived to ensure the almost sure asymptotical stability for the dynamics of estimator error. Several suitable parameters update laws are found by the adaptive feedback control technique. Finally, a simulation example is provided to illustrate the effectiveness of the proposed adaptive estimation method.