Unitary-Invariant Decomposition of Reducible Total Least Squares Core Problems

TL;DR

This paper introduces a systematic, invariant method for decomposing total least squares core problems into unique irreducible components using spectral analysis over the complex field.

Contribution

It develops a complete framework for the exact, unitary-invariant decomposition of TLS core problems into irreducible subproblems, addressing an open question in the field.

Findings

Decomposition into irreducible components is unique up to unitary transformations and permutations.

The spectral structure of covariance operators enables identification of all complex indivisible subspaces.

The framework partially resolves an open problem on invariant decomposition of TLS core problems.

Abstract

The analysis of a total least square problem (TLS) can be reduced to that of an associated core problem, which typically has lower dimension and improved solubility properties. Nevertheless, even a core problem may remain reducible, admitting further decomposition into irreducible component subproblems with simpler structure and better analytical properties. However, no systematic and invariant procedure is available for identifying all such component subproblems, either over either real or complex field.In this paper, a complete and constructive framework is developed for the exact decomposition of TLS core problems into unitary-unique irreducible component subproblems.By working over the complex field and exploiting the spectral structure of covariance operators associated with C-subset subproblems, the proposed strategy yields all complex indivisible subspaces which will lead to irreducible component sub-problems. As a consequence, we prove that irreducible component subproblems are uniquely determined up to unitary transformations and permutation, thereby partially resolving an open question left in Yu, Jing. SIAM J. Matrix Anal. Appl., 46 (2025).