Wavelength detection in FBG sensor networks using least squares support vector regression

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	Wavelength detection in FBG sensor networks using least squares support vector regression
	Chen, Jing ; Jiang, Hao ; Liu, Tundong ; Fu, Xiaoli ; Liu TD(刘暾东)
刊名	http://dx.doi.org/10.1088/2040-8978/16/4/045402
	2014
关键词	TUNABLE FILTER INTERROGATION PERFORMANCE MACHINES ALGORITHM
英文摘要	A wavelength detection method for a wavelength division multiplexing (WDM) fiber Bragg grating (FBG) sensor network is proposed based on least squares support vector regression (LS-SVR). As a kind of promising machine learning technique, LS-SVR is employed to approximate the inverse function of the reflection spectrum. The LS-SVR detection model is established from the training samples, and then the Bragg wavelength of each FBG can be directly identified by inputting the measured spectrum into the well-trained model. We also discuss the impact of the sample size and the preprocess of the input spectrum on the performance of the training effectiveness. The results demonstrate that our approach is effective in improving the accuracy for sensor networks with a large number of FBGs.
语种	英语
出版者	IOP PUBLISHING LTD
内容类型	期刊论文
源URL	[http://dspace.xmu.edu.cn/handle/2288/92705]
专题	信息技术－已发表论文
推荐引用方式 GB/T 7714	Chen, Jing,Jiang, Hao,Liu, Tundong,et al. Wavelength detection in FBG sensor networks using least squares support vector regression[J]. http://dx.doi.org/10.1088/2040-8978/16/4/045402,2014.
APA	Chen, Jing,Jiang, Hao,Liu, Tundong,Fu, Xiaoli,&刘暾东.(2014).Wavelength detection in FBG sensor networks using least squares support vector regression.http://dx.doi.org/10.1088/2040-8978/16/4/045402.
MLA	Chen, Jing,et al."Wavelength detection in FBG sensor networks using least squares support vector regression".http://dx.doi.org/10.1088/2040-8978/16/4/045402 (2014).