title: Global Mittag-Leffler stability and synchronization of memristor-based fractional-order neural networks.
abstract: The present paper introduces memristor-based fractional-order neural networks. The conditions on the global Mittag-Leffler stability and synchronization are established by using Lyapunov method for these networks. The analysis in the paper employs results from the theory of fractional-order differential equations with discontinuous right-hand sides. The obtained results extend and improve some previous works on conventional memristor-based recurrent neural networks.
authors: School of Automation, Huazhong University of Science and Technology, Wuhan 430074, China; Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China, Wuhan 430074, China. Electronic address: chenjiejie118@gmail.com.
authors: Jiejie
authors: J
authors: Chen
authors: School of Automation, Huazhong University of Science and Technology, Wuhan 430074, China; Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China, Wuhan 430074, China. Electronic address: hustzgzeng@gmail.com.
authors: Zhigang
authors: Z
authors: Zeng
authors: School of Automation, Huazhong University of Science and Technology, Wuhan 430074, China; Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China, Wuhan 430074, China.
authors: Ping
authors: P
authors: Jiang
mesh_terms: D000465:Algorithms; D008959:Models, Neurological; D016571:Neural Networks, Computer; D013997:Time Factors
keywords: Filippov’s solution; Fractional-order; Global Mittag-Leffler stability; Memristor-based neural networks; Synchronization