一类比例时滞随机神经网络的均方指数同步及应用

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Mean Square Exponential Synchronization of a Class of Proportional Delay Stochastic Neural Networks and Its Application

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Abstract:

A class of proportional delay inertial stochastic neural networks is used as the driving-response systems. The mean square exponential synchronization of the studied system is analyzed by reducing the order method, adopting a state feedback controller, utilizing Itô integral, constructing a novel Lyapunov functional, and utilizing the properties of calculus. The criteria for determining the mean square exponential synchronization of the studied system are obtained. Finally, the accuracy of the judgment criteria obtained is verified through a numerical example and simulations, and the application of the studied exponential synchronization in image encryption and decryption is presented.

Key words: stochastic neural networks, inertia term, mean square exponential synchronization, proportional delay, encryption and decryption of image

CLC Number:

O175.13

Hongyue Ren, Liqun Zhou. Mean Square Exponential Synchronization of a Class of Proportional Delay Stochastic Neural Networks and Its Application[J].Acta mathematica scientia,Series A, 2025, 45(3): 888-901.

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[1]	Xingshou Huang,Ricai Luo,Wusheng Wang. Stability Analysis for a Class Neural Network with Proportional Delay Based on the Gronwall Integral Inequality [J]. Acta mathematica scientia,Series A, 2020, 40(3): 824-832.
[2]	WANG Hong-Chu, HU Shi-Geng. Exponential Stability for Stochastic Neural Networks with Multiple Delays: an LMI Approach [J]. Acta mathematica scientia,Series A, 2010, 30(1): 42-53.