Name
Abstract | ||
|---|---|---|
In this paper, we present a new method for numerical differentiation of bivariate periodic functions when a set of noisy data is given. TSVD is chosen as the needed regularization technique. It turns out the new method coincides with some type of truncated Fourier series approach. A numerical example is also given to show the efficiency of the method. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1109/CSO.2009.174 | CSO (1) |
Keywords | Field | DocType |
mollification method,needed regularization technique,fourier series,new mollification method,2d periodic function,ill-posed problem,truncated fourier series approach,regularization technique,tsvd method,differentiation,numerical differentiation,bivariate periodic function,numerical example,noisy data,new method,periodic functions,statistics,finance,mathematics,knowledge engineering,noise measurement,inverse problems,business,probability density function,data mining,convergence | Convergence (routing),Numerical differentiation,Periodic function,Mathematical optimization,Mathematical analysis,Fourier series,Regularization (mathematics),Inverse problem,Bivariate analysis,Probability density function,Mathematics | Conference |
Volume | ISBN | Citations |
1 | 978-0-7695-3605-7 | 0 |
PageRank | References | Authors |
0.34 | 1 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Zhenyu Zhao | 1 | 12 | 7.86 |
| Ze-hong Meng | 2 | 19 | 2.07 |
| Li Xu | 3 | 0 | 0.34 |
| Junfeng Liu | 4 | 17 | 10.40 |