State Estimation of Discrete-Time Fractional-Order Nonautonomous Neural Networks With Time Delays
研究了具有泄漏和离散时滞的离散时间分数阶非自治神经网络的状态估计问题，通过建立新的不等式和线性矩阵不等式方法，给出了误差系统全局渐近稳定的充分条件，并用数值仿真验证了结果。
This article is dedicated to an investigation of state estimation for discrete-time fractional-order nonautonomous neural networks (DFNNNs) with leakage and discrete delays. To this end, some inequalities with more free parameters are obtained based on results related to nabla fractional difference, which considerably extend the existing results. In light of the effective estimator, some sufficient conditions to ensure the global asymptotic stability of the error system are obtained to solve the state estimation problem for DFNNNs by means of the linear matrix inequality (LMI) and the established inequalities. Finally, the theoretical results are verified by numerical simulations.