Numerical differentiation of noisy data with local optimum by data segmentation

被引：1
|
作者：
Zhang, Jianhua [1 ,2 ]
Que, Xiufu [1 ,2 ]
Chen, Wei [1 ]
Huang, Yuanhao [1 ]
Yang, Lianqiao [1 ]
机构：
[1] Shanghai Univ, Minist Educ, Key Lab Adv Display & Syst Applicat, Shanghai 200072, Peoples R China
[2] Shanghai Univ, Sch Mech & Elect Engn & Automat, Shanghai 200072, Peoples R China
来源：
JOURNAL OF SYSTEMS ENGINEERING AND ELECTRONICS | 2015年 / 26卷 / 04期
关键词：
numerical differentiation; noisy data; local optimum; data segmentation; FOURIER-TRANSFORM; B-SPLINES; MCMC;
D O I：
10.1109/JSEE.2015.00094
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
A new numerical differentiation method with local optimum by data segmentation is proposed. The segmentation of data is based on the second derivatives computed by a Fourier development method. A filtering process is used to achieve acceptable segmentation. Numerical results are presented by using the data segmentation method, compared with the regularization method. For further investigation, the proposed algorithm is applied to the resistance capacitance (RC) networks identification problem, and improvements of the result are obtained by using this algorithm.
引用
收藏
页码：868 / 876
页数：9
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