Abstract
This paper states with the objective of investigating the finite-time stabilization and fixed-time stabilization analysis for stochastic second-order neutral-type neural networks with mixed delays. By using a variable transformation, we first rewrite the original system as a first-order differential system. By designing some feedback control laws inputs, stochastic analysis theory, finite-time stability theorem, fixed-time stability theorem, based on Lyapunov Functionals and inequalities techniques, new sufficient conditions ensuring the finite/fixed-time stabilization of the suggested system are given. Finally, the developed main control schemes, the finite/fixed-time stabilization for the stochastic Neural Networks are confirmed by two simulations examples.
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Funding
This work was jointly supported by the National Natural Science Foundation of China (62173139, 61773217), the Science and Technology Innovation Program of Hunan Province (2021RC4030), Hunan Provincial Science and Technology Project Foundation (2019RS1033).
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Aouiti, C., Jallouli, H., Zhu, Q. et al. New Results on Finite/Fixed-Time Stabilization of Stochastic Second-Order Neutral-Type Neural Networks with Mixed Delays. Neural Process Lett 54, 5415–5437 (2022). https://doi.org/10.1007/s11063-022-10868-9
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DOI: https://doi.org/10.1007/s11063-022-10868-9