Quan Xu

Dr. Quan Xu

School of Microelectronics and Control Engineering, Changzhou University, Changzhou, Jiangsu, China
orcid

Research Focus & Metrics

Academic Career Length

18Years (2009-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 January 2017 in Chaos, Solitons & Fractals
Verified
Journal Article
Closed access
BBBocheng Bao
Bocheng Bao
HBHan Bao
Han Bao
Ning WangNing Wang
Ning Wang
MCMo Chen
Mo Chen
Quan XuQuan Xu
Quan Xu

1 February 2016 in Chaos, Solitons & Fractals
Verified
Journal Article
Closed access
Quan XuQuan Xu
Quan Xu
YLYi Lin
Yi Lin
BBBocheng Bao
Bocheng Bao
MCMo Chen
Mo Chen

1 June 2016 in Electronics Letters
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Journal Article
Open access
PDF file
BBBocheng Bao
Bocheng Bao
Quan XuQuan Xu
Quan Xu
HBHan Bao
Han Bao
MCMo Chen
Mo Chen
A memristive Chua's circuit regarded as a paradigm is reconsidered to exhibit its extreme multistability in this Letter. Memristor initial state‐dependent dynamics is analysed and the coexistence of infinitely many attractors related to memristor initial states is revealed by numerical simulations and circuit simulations. The dynamical behaviour just reflects the emergence of extreme multistability in the memristive circuit.

4 August 2016 in Nonlinear Dynamics
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Journal Article
Closed access
PDF file
BBBocheng Bao
Bocheng Bao
TJTao Jiang
Tao Jiang
Quan XuQuan Xu
Quan Xu
MCMo Chen
Mo Chen
HWHuagan Wu
Huagan Wu
Yihua HuYihua Hu
Yihua Hu

22 February 2015 in Nonlinear Dynamics
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Journal Article
Closed access
PDF file
MCMo Chen
Mo Chen
MLMengyuan Li
Mengyuan Li
QYQing Yu
Qing Yu
BBBocheng Bao
Bocheng Bao
Quan XuQuan Xu
Quan Xu
JWJiang Wang
Jiang Wang

23 August 2017 in Frontiers in Computational Neuroscience
Verified
Journal Article
Open access
BBBocheng Bao
Bocheng Bao
HQHui Qian
Hui Qian
Quan XuQuan Xu
Quan Xu
MCMo Chen
Mo Chen
JWJiang Wang
Jiang Wang
YYYajuan Yu
Yajuan Yu
A new hyperbolic-type memristor emulator is presented and its frequency-dependent pinched hysteresis loops are analyzed by numerical simulations and confirmed by hardware experiments. Based on the emulator, a novel hyperbolic-type memristor based 3-neuron Hopfield neural network (HNN) is proposed, which is achieved through substituting one coupling-connection weight with a memristive synaptic weight. It is numerically shown that the memristive HNN has a dynamical transition from chaotic, to periodic, and further to stable point behaviors with the variations of the memristor inner parameter, implying the stabilization effect of the hyperbolic-type memristor on the chaotic HNN. Of particular interest, it should be highly stressed that for different memristor inner parameters, different coexisting behaviors of asymmetric attractors are emerged under different initial conditions, leading to the existence of multistable oscillation states in the memristive HNN. Furthermore, by using commercial discrete components, a nonlinear circuit is designed and PSPICE circuit simulations and hardware experiments are performed. The results simulated and captured from the realization circuit are consistent with numerical simulations, which well verify the facticity of coexisting asymmetric attractors’ behaviors.