On regularization methods of EM-Kaczmarz type

Abstract

We consider regularization methods of Kaczmarz type in connection with the expectation-maximization (EM) algorithm for solving ill-posed equations. For noisy data, our methods are stabilized extensions of the well established ordered-subsets expectation-maximization iteration (OS-EM). We show monotonicity properties of the methods and present a numerical experiment which indicates that the extended OS-EM methods we propose are much faster than the standard EM algorithm.

18 pages, 6 figures; On regularization methods of EM-Kaczmarz type

References in corpus (2)

• Regularization of systems of nonlinear ill-posed equations: I. Convergence Analysis
• Regularization of systems of nonlinear ill-posed equations: II. Applications

Cited by in corpus (3)

• On projective Landweber-Kaczmarz methods for solving systems of nonlinear ill-posed equations
• Modified iterated Tikhonov methods for solving systems of nonlinear ill-posed equations
• Two new non-negativity preserving iterative regularization methods for ill-posed inverse problems