title: Dynamic behaviors of memristor-based recurrent neural networks with time-varying delays.
abstract: The paper introduces a general class of memristor-based recurrent neural networks with time-varying delays. Conditions on the nondivergence and global attractivity are established by using local inhibition, respectively. Moreover, exponential convergence of the networks is studied by using local invariant sets. The analysis in the paper employs results from the theory of differential equations with discontinuous right-hand sides as introduced by Filippov. The obtained results extend some previous works on conventional recurrent neural networks.
authors.affiliation: Department of Control Science and Engineering, Huazhong University of Science and Technology, Wuhan 430074, China. alequ@126.com
authors.forename: Ailong
authors.initials: A
authors.lastname: Wu
authors.forename: Zhigang
authors.initials: Z
authors.lastname: Zeng
mesh_terms: D000465:Algorithms; D016248:Computer Storage Devices / Q000145:classification; D004560:Electricity; D016571:Neural Networks, Computer; D017711:Nonlinear Dynamics; D013997:Time Factors