Exponential synchronization of memristive neural networks with time-varying delays via quantized sliding-mode control. Academic Article

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.

authors

• Huang, Tingwen

published proceedings

• Neural Netw

author list (cited authors)

• Sun, B. o., Wang, S., Cao, Y., Guo, Z., Huang, T., & Wen, S.

citation count

• 18

complete list of authors

• Sun, Bo||Wang, Shengbo||Cao, Yuting||Guo, Zhenyuan||Huang, Tingwen||Wen, Shiping

publication date

• June 2020

publisher

• Elsevier  Publisher

published in

• Neural Networks  Journal

keywords

• Algorithms
• Exponential Synchronization
• Memristive Neural Network
• Neural Networks, Computer
• Quantization Function
• Super-twisting Algorithm
• Time Factors
• Time-varying Delay

PubMed Central ID

• 32224322

Digital Object Identifier (DOI)

• 10.1016/j.neunet.2020.03.014

start page

• 163

end page

• 169

volume

• 126

URL

• http://dx.doi.org/10.1016/j.neunet.2020.03.014