Finite-Time Function Projective Synchronization of Unknown Cohen-Grossberg Neural Networks With Time Delays and Stochastic Disturbances and Its Application in Secure Communication

ZHANG Yamei; HAO Tao; YIN Sibei; ZHANG Meng

doi:10.21656/1000-0887.410025

Volume 41 Issue 12

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ZHANG Yamei, HAO Tao, YIN Sibei, ZHANG Meng. Finite-Time Function Projective Synchronization of Unknown Cohen-Grossberg Neural Networks With Time Delays and Stochastic Disturbances and Its Application in Secure Communication[J]. Applied Mathematics and Mechanics, 2020, 41(12): 1405-1416. doi: 10.21656/1000-0887.410025

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Finite-Time Function Projective Synchronization of Unknown Cohen-Grossberg Neural Networks With Time Delays and Stochastic Disturbances and Its Application in Secure Communication

doi: 10.21656/1000-0887.410025

¹Department of Electrical and Automation, Shandong Labor Vocational and Technical College, Jinan 250000, P.R.China;²School of Automation, Shenyang Aerospace University, Shenyang 110000, P.R.China

Received Date: 2020-01-13
Rev Recd Date: 2020-11-04
Publish Date: 2020-12-01

Abstract

Abstract

The finite-time function projective synchronization of unknown Cohen-Grossberg neural networks with time delays and stochastic disturbances was investigated. A hybrid control scheme combining open-loop control and feedback control was designed to guarantee that the drive and response networks can be synchronized up to a scaling function in a finite time with parameter identification by means of the finite-time stability theory. Besides, the upper bounds of the settling time of synchronization were estimated. Finally, the corresponding numerical simulation and its application in secure communication were provided to demonstrate the validity of the presented synchronization method.
- synchronization,
- Cohen-Grossberg neural network,
- finite time,
- secure communication

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References(21)

References

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