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Numerical differentiation of noisy data with local optimum by data segmentation

Numerical differentiation of noisy data with local optimum by data segmentation
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摘要 A new numerical differentiation method with local opti- mum by data segmentation is proposed. The segmentation of data is based on the second derivatives computed by a Fourier devel- opment 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. A new numerical differentiation method with local opti- mum by data segmentation is proposed. The segmentation of data is based on the second derivatives computed by a Fourier devel- opment 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.
出处 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 2015年第4期868-876,共9页 系统工程与电子技术(英文版)
基金 supported by the National Basic Research Program of China(2011CB013103)
关键词 numerical differentiation noisy data local optimum data segmentation. numerical differentiation, noisy data, local optimum,data segmentation.
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