A modification on strictly positive definite RBF-DQ method based on matrix decomposition
The infinitely smooth RBF methods are theoretically spectrally accurate for applying on scattered data interpolation, and also partial differential equations, but the interpolation matrices of them are extremely ill-conditioned especially for strictly positive definite ones. Therefore, an efficient technique to recover this problem is too important. In this article, a general matrix decomposition method for strictly positive definite RBFs interpolation matrix has been investigated. In the current decomposition the RBFs interpolation matrix is obtained as multiplication of some well-conditioned matrices. This decomposition has been applied to RBF-DQ method and its results more accurate weight coefficients when we involve solving PDEs.
- 원문이 없습니다.
- DOI : http://dx.doi.org/10.1016/j.enganabound.2017.01.001
- Elsevier : 저널> 권호 > 논문
NDSL에서는 해당 원문을 복사서비스하고 있습니다. 위의 원문복사신청 또는 장바구니 담기를 통하여 원문복사서비스 이용이 가능합니다.
- 이 논문과 함께 출판된 논문 + 더보기