Normalized implicit eigenvector least squares operators for noisy scattered data: radial basis functions

Least-square-based radial basis collocat

Least-square-based radial basis collocation method for solving inverse problems of Laplace equation from noisy data

✍ Xian-Zhong Mao; Zi Li 📂 Article 📅 2010 🏛 John Wiley and Sons 🌐 English ⚖ 368 KB

## Abstract The inverse problem of 2D Laplace equation involves an estimation of unknown boundary values or the locations of boundary shape from noisy observations on over‐specified boundary or internal data points. The application of radial basis collocation method (RBCM), one of meshless and non‐