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1

College of Mathematics and Information Science, Shaanxi Normal University, Xi’an 710119, China

2

Department of Applied Mathematics, Huainan Normal University, Huainan 232038, China

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School of Electronic Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China





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Author to whom correspondence should be addressed.



Academic Editors: J. A. Tenreiro Machado and António M. Lopes

Abstract In this paper, synchronization for a class of uncertain fractional-order neural networks subject to external disturbances and disturbed system parameters is studied. Based on the fractional-order extension of the Lyapunov stability criterion, an adaptive synchronization controller is designed, and fractional-order adaptation law is proposed to update the controller parameter online. The proposed controller can guarantee that the synchronization errors between two uncertain fractional-order neural networks converge to zero asymptotically. By using some proposed lemmas, the quadratic Lyapunov functions are employed in the stability analysis. Finally, numerical simulations are presented to confirm the effectiveness of the proposed method. View Full-Text

Keywords: fractional-order neural network; adaptive control; synchronization fractional-order neural network; adaptive control; synchronization





Autor: Heng Liu 1,2, Shenggang Li 1,* , Hongxing Wang 2, Yuhong Huo 2 and Junhai Luo 3

Fuente: http://mdpi.com/



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