Adaptive Intermittent Stabilization for State-Dependent Switched Inertial Neural Networks With Mixed Infinite Delays
针对带有混合无限时滞的状态依赖切换惯性神经网络，构造了能压缩无限时滞的Lyapunov泛函，设计了自适应间歇控制器，给出了指数稳定的充分条件。
Infinite delays, especially mixed infinite delays (MIDs), always pose a great challenge for exponentially stability analysis of neural networks (NNs). In this article, we construct a new Lyapunov functional that contains an auxiliary function with the ability to compress infinite time delays to bounded ones, which can remove some of the previous assumptions on NNs systems. Then, several new sufficient conditions to guarantee the exponential stabilization of state-dependent switched inertial NNs with MIDs are derived under the designed adaptive intermittent controller. Finally, numerical simulations are provided to illustrate the validity of the obtained results.