Accuracy-preassigned fixed-time synchronization of inertial neural networks with time-varying leakage delays and proportional delays

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Abstract

This work established synchronization criteria for master-slave inertial neural networks with leakage time-varying delays and proportional delays, The solution employed a direct analysis method based on parameterized system solutions. The derived synchronization conditions consisted of only a few simple inequalities, which were easy to solve.Based on the adopted approach, a novel class of synchronization controllers was designed for proportional delays without constructing any complex functionals. Using the proposed method, leakage delays could be transformed into their maximum absolute values, enabling the derivation of delay-dependent conditions without any intricate treatment of leakage delays. Furthermore, it was noteworthy that this paper presented the first investigation into this problem using the proposed method, and the technique employed was novel. Finally, numerical simulations were provided to verify the effectiveness of the proposed method.

Keywords

inertial neural networks / leakage delay / proportional delays / a direct analysis method grounded in parameterized system solutions / fixed-time synchronization with preassigned accuracy

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