Adaptive Intermittent Stabilization for State-Dependent Switched Inertial Neural Networks With Mixed Infinite Delays

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.