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A Bayesian regularized artificial neural network for adaptive optics forecasting
Sun, Zhi1,3; Chen, Ying2; Li, Xinyang2; Qin, Xiaolin1; Wang, Huiyong1,3,4
2017
发表期刊Optics Communications
ISSN0030-4018
卷号382页码:519-527
摘要Real-time adaptive optics is a technology for enhancing the resolution of ground-based optical telescopes and overcoming the disturbance of atmospheric turbulence. The performance of the system is limited by delay errors induced by the servo system and photoelectrons noise of wavefront sensor. In order to cut these delay errors, this paper proposes a novel model to forecast the future control voltages of the deformable mirror. The predictive model is constructed by a multi-layered back propagation network with Bayesian regularization (BRBP). For the purpose of parallel computation and less disturbance, we adopt a number of sub-BP neural networks to substitute the whole network. The Bayesian regularized network assigns a probability to the network weights, allowing the network to automatically and optimally penalize excessively complex models. The simulation results show that the BRBP introduces smaller mean absolute percentage error (MAPE) and mean square errors (MSE) than other typical algorithms. Meanwhile, real data analysis results show that the BRBP model has strong generalization capability and parallelism. © 2016 Elsevier B.V.
关键词Adaptive control systems - Atmospheric turbulence - Backpropagation - Complex networks - Errors - Mean square error - Network layers - Neural networks - Parallel processing systems
收录类别SCI ; Ei
语种英语
文献类型期刊论文
条目标识符http://ir.ioe.ac.cn/handle/181551/8862
专题自适应光学技术研究室(八室)
作者单位1.Chengdu Institute of Computer Applications, Chinese Academy of Sciences, Chengdu; 610041, China;
2.Institute of Optics and Electronics, Chinese Academy of Sciences, Chengdu; 610209, China;
3.University of Chinese Academy of Sciences, Beijing; 100049, China;
4.Guangxi Key Laboratory of Cryptography and Information Security, Guilin University of Electronic Technology, Guilin; 541004, China
推荐引用方式
GB/T 7714
Sun, Zhi,Chen, Ying,Li, Xinyang,et al. A Bayesian regularized artificial neural network for adaptive optics forecasting[J]. Optics Communications,2017,382:519-527.
APA Sun, Zhi,Chen, Ying,Li, Xinyang,Qin, Xiaolin,&Wang, Huiyong.(2017).A Bayesian regularized artificial neural network for adaptive optics forecasting.Optics Communications,382,519-527.
MLA Sun, Zhi,et al."A Bayesian regularized artificial neural network for adaptive optics forecasting".Optics Communications 382(2017):519-527.
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