In this paper, the problem of reconstructing numerical derivatives from noisy data is considered. A new framework of mollification methods based on the L generalized solution regularization methods is proposed. A spec...In this paper, the problem of reconstructing numerical derivatives from noisy data is considered. A new framework of mollification methods based on the L generalized solution regularization methods is proposed. A specific algorithm for the first three derivatives is presented in the paper, in which a modification of TSVD, termed cTSVD is chosen as the regularization technique. Numerical examples given in the paper verify the theoretical results and show efficiency of the new method.展开更多
考虑由扰动数据重构原函数的导数问题.基于L-广义解正则化理论,提出了一个新的磨光方法的框架.给出一个具体的求解前3阶导数的算法,其中正则化策略选择了一种改进的TSVD(truncated singular value decomposition)方法(典则TSVD方法).数...考虑由扰动数据重构原函数的导数问题.基于L-广义解正则化理论,提出了一个新的磨光方法的框架.给出一个具体的求解前3阶导数的算法,其中正则化策略选择了一种改进的TSVD(truncated singular value decomposition)方法(典则TSVD方法).数值结果进一步验证了理论结果及新方法的有效性.展开更多
文摘In this paper, the problem of reconstructing numerical derivatives from noisy data is considered. A new framework of mollification methods based on the L generalized solution regularization methods is proposed. A specific algorithm for the first three derivatives is presented in the paper, in which a modification of TSVD, termed cTSVD is chosen as the regularization technique. Numerical examples given in the paper verify the theoretical results and show efficiency of the new method.
文摘考虑由扰动数据重构原函数的导数问题.基于L-广义解正则化理论,提出了一个新的磨光方法的框架.给出一个具体的求解前3阶导数的算法,其中正则化策略选择了一种改进的TSVD(truncated singular value decomposition)方法(典则TSVD方法).数值结果进一步验证了理论结果及新方法的有效性.
