## Journals

- Advances in Mathematics of Communications
- Big Data & Information Analytics
- Communications on Pure & Applied Analysis
- Discrete & Continuous Dynamical Systems - A
- Discrete & Continuous Dynamical Systems - B
- Discrete & Continuous Dynamical Systems - S
- Evolution Equations & Control Theory
- Foundations of Data Science
- Inverse Problems & Imaging
- Journal of Computational Dynamics
- Journal of Dynamics & Games
- Journal of Geometric Mechanics
- Journal of Industrial & Management Optimization
- Journal of Modern Dynamics
- Kinetic & Related Models
- Mathematical Biosciences & Engineering
- Mathematical Control & Related Fields
- Mathematical Foundations of Computing
- Networks & Heterogeneous Media
- Numerical Algebra, Control & Optimization
- AIMS Mathematics
- Conference Publications
- Electronic Research Announcements
- Mathematics in Engineering

### Open Access Journals

IPI

Conjugate Gradient is widely used as a regularizing technique for
solving linear systems with ill-conditioned coefficient matrix and right-hand side vector perturbed by noise.
It enjoys a good convergence rate and computes quickly an iterate, say $x_{k_{opt}}$, which minimizes the
error with respect to the exact solution. This behavior can be a disadvantage in
the regularization context, because also the high-frequency components of the noise enter
quickly the computed solution, leading to a difficult detection of $k_{opt}$
and to a sharp increase of the error after the $k_{opt}$th iteration. In this paper we propose an inner-outer algorithm based on a sequence of restarted Conjugate Gradients, with the
aim of overcoming this drawback. A numerical experimentation validates the effectiveness of the proposed algorithm.

## Year of publication

## Related Authors

## Related Keywords

[Back to Top]