A conjugate subgradient algorithm with adaptive preconditioning for the least absolute shrinkage and selection operator minimization |
| |
Authors: | A Mirone P Paleo |
| |
Institution: | 1.European Synchrotron Radiation Facility,Grenoble Cedex,France |
| |
Abstract: | This paper describes a new efficient conjugate subgradient algorithm which minimizes a convex function containing a least squares fidelity term and an absolute value regularization term. This method is successfully applied to the inversion of ill-conditioned linear problems, in particular for computed tomography with the dictionary learning method. A comparison with other state-of-art methods shows a significant reduction of the number of iterations, which makes this algorithm appealing for practical use. |
| |
Keywords: | |
本文献已被 SpringerLink 等数据库收录! |
|