Abstract
| Original language | English |
|---|---|
| Article number | 109 |
| Number of pages | 10 |
| Journal | The European Physical Journal B - Condensed Matter and Complex Systems |
| Volume | 88 |
| Early online date | 4 May 2015 |
| DOIs | |
| Publication status | Published - May 2015 |
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Keywords
- Statistical and Nonlinear Physics
Cite this
Anti-synchronization for stochastic memristor-based neural networks with non-modeled dynamics via adaptive control approach. / Zhao, Hui; Li, Lixiang; Peng, Haipeng; Kurths, Jurgen; Xiao, Jinghua; Yang, Yixian.
In: The European Physical Journal B - Condensed Matter and Complex Systems , Vol. 88, 109, 05.2015.Research output: Contribution to journal › Article
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TY - JOUR
T1 - Anti-synchronization for stochastic memristor-based neural networks with non-modeled dynamics via adaptive control approach
AU - Zhao, Hui
AU - Li, Lixiang
AU - Peng, Haipeng
AU - Kurths, Jurgen
AU - Xiao, Jinghua
AU - Yang, Yixian
N1 - The authors thank all the editor and the anonymous referees for their constructive comments and valuable suggestions, which are helpful to improve the quality of this paper. The work is supported by the National Natural Science Foundation of China (Grant Nos. 61170269, 61472045), the Beijing Higher Education Young Elite Teacher Project (Grant No. YETP0449), and the Beijing Natural Science Foundation (Grant No. 4142016). All authors contributed equally to the paper.
PY - 2015/5
Y1 - 2015/5
N2 - In this paper, exponential anti-synchronization in mean square of an uncertain memristor-based neural network is studied. The uncertain terms include non-modeled dynamics with boundary and stochastic perturbations. Based on the differential inclusions theory, linear matrix inequalities, Gronwall’s inequality and adaptive control technique, an adaptive controller with update laws is developed to realize the exponential anti-synchronization. Adaptive controller can adjust itself behavior to get the best performance, according to the environment is changing or the environment has changed, which has the ability to adapt to environmental change. Furthermore, a numerical example is provided to validate the effectiveness of the proposed method
AB - In this paper, exponential anti-synchronization in mean square of an uncertain memristor-based neural network is studied. The uncertain terms include non-modeled dynamics with boundary and stochastic perturbations. Based on the differential inclusions theory, linear matrix inequalities, Gronwall’s inequality and adaptive control technique, an adaptive controller with update laws is developed to realize the exponential anti-synchronization. Adaptive controller can adjust itself behavior to get the best performance, according to the environment is changing or the environment has changed, which has the ability to adapt to environmental change. Furthermore, a numerical example is provided to validate the effectiveness of the proposed method
KW - Statistical and Nonlinear Physics
U2 - 10.1140/epjb/e2015-50798-9
DO - 10.1140/epjb/e2015-50798-9
M3 - Article
VL - 88
JO - The European Physical Journal B - Condensed Matter and Complex Systems
JF - The European Physical Journal B - Condensed Matter and Complex Systems
SN - 1434-6028
M1 - 109
ER -