Exponential synchronization of memristive neural networks with time-varying delays via quantized sliding-mode control. (June 2020)

• Record Type: Journal Article
• Authors: Sun, Bo; Wang, Shengbo; Cao, Yuting; Guo, Zhenyuan; Huang, Tingwen; Wen, Shiping
• Is Part Of: Neural networks. Volume 126(2020)
• Page Start: 163
• Page End: 169
• Publication Date: 2020-06
• Subjects: Memristive neural network -- Time-varying delay -- Super-twisting algorithm -- Quantization function -- Exponential synchronization; Neural computers -- Periodicals; Neural networks (Computer science) -- Periodicals; Neural networks (Neurobiology) -- Periodicals; Nervous System -- Periodicals; Ordinateurs neuronaux -- Périodiques; Réseaux neuronaux (Informatique) -- Périodiques; Réseaux neuronaux (Neurobiologie) -- Périodiques; Neural computers; Neural networks (Computer science); Neural networks (Neurobiology); Periodicals; 006.32
• DOI: 10.1016/j.neunet.2020.03.014
• Languages: English
• ISSNs: 0893-6080

Abstract

Abstract: In the paper, exponential synchronization issue is considered for memristive neural networks (MNNs) with time-varying delays via quantized sliding-mode algorithm. Quantized Sliding-mode controller is introduced to ensure the slave system can be exponentially synchronized with the host system via the super-twisting algorithm, which has been proved in the main results. Quantization function consists of uniform quantizer and logarithmic quantizer. Simulation results are given with comparisons between two quantizers in the end.