Restarted Nonnegativity Preserving Tensor Splitting Methods via Relaxed Anderson Acceleration for Solving Multi-linear Systems

TL;DR

This paper introduces a new tensor splitting method with relaxed Anderson acceleration that preserves nonnegativity at each step, improves convergence, and demonstrates effectiveness through numerical experiments.

Contribution

The paper proposes a novel nonnegativity-preserving tensor splitting method with relaxed Anderson acceleration and provides convergence analysis.

Findings

Effective in numerical experiments

Preserves nonnegativity at each iteration

Improves convergence over existing methods

Abstract

Multilinear systems play an important role in scientific calculations of practical problems. In this paper, we consider a tensor splitting method with a relaxed Anderson acceleration for solving multilinear systems. The new method preserves nonnegativity for every iterative step and improves the existing ones. Furthermore, the convergence analysis of the proposed method is given. The new algorithm performs effectively for numerical experiments.