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Some Further Results on Fixed-Time Synchronization of Neural Networks with Stochastic Perturbations

Some Further Results on Fixed-Time Synchronization of Neural Networks with Stochastic Perturbations
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摘要 In this paper, fixed-time (FXT) synchronization issue of a type of neural networks (NNs) with stochastic perturbations is considered. First, we obtained some novel sufficient criteria to guarantee the FXT synchronization of considered networks via introducing two types of controllers and employing some inequality techniques. Lastly, our theoretical results are verified via giving two numerical examples with their Matlab simulations. In this paper, fixed-time (FXT) synchronization issue of a type of neural networks (NNs) with stochastic perturbations is considered. First, we obtained some novel sufficient criteria to guarantee the FXT synchronization of considered networks via introducing two types of controllers and employing some inequality techniques. Lastly, our theoretical results are verified via giving two numerical examples with their Matlab simulations.
作者 Aminamuhan Abudireman Mairemunisa Abudusaimaiti Wanjuan Sun Jiangyuan Zhao Yuanshuang Zhang Abdujelil Abdurahman Aminamuhan Abudireman;Mairemunisa Abudusaimaiti;Wanjuan Sun;Jiangyuan Zhao;Yuanshuang Zhang;Abdujelil Abdurahman(College of Mathematics and System Sciences, Xinjiang University, Urumqi, China)
出处 《Journal of Applied Mathematics and Physics》 2022年第1期200-218,共19页 应用数学与应用物理(英文)
关键词 Fixed-Time Stability Stochastic Perturbation SYNCHRONIZATION Neural Network Fixed-Time Stability Stochastic Perturbation Synchronization Neural Network
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