Adaptive intermittent stabilization for state-dependent switched inertial neural networks with mixed infinite delays
IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2024•ieeexplore.ieee.org
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 …
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 …
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.
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