학술저널
A WEIGHTED GLOBAL GENERALIZED CROSS VALIDATION FOR GL-CGLS REGULARIZATION
- 충청수학회
- Journal of the Chungcheong Mathematical Society
- Volume 29, No. 1
-
2016.0259 - 71 (13 pages)
- 2
To obtain more accurate approximation of the true images in the deblurring problems, the weighted global generalized cross validation(GCV) function to the inverse problem with multiple right-hand sides is suggested as an efficient way to determine the regularization parameter. We analyze the experimental results for many test problems and was able to obtain the globally useful range of the weight when the preconditioned global conjugate gradient linear least squares(Gl-CGLS) method with the weighted global GCV function is applied.
1. Introduction
2. Weighted global GCV method for regularization parameters
3. Preconditioned Gl-CGLS regularization method with weighted global GCV
4. Numerical experiments
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