Yan‐Fei Jing

B. Carpentieri, Y. -F. Jing, T. -Z. Huang et al.

We present economical iterative algorithms built on the Biconjugate $A$-Orthonormalization Procedure for real unsymmetric and complex non-Hermitian systems. The principal characteristics of the developed solvers is that they are fast convergent and cheap in memory. We report on a large combination of numerical experiments to demonstrate that the proposed family of methods is highly competitive and often superior to other popular algorithms built upon the Arnoldi method and the biconjugate Lanczos procedures for unsymmetric linear sytems.

Sijia Yu, Bruno Carpentieri, Yan-Fei Jing

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).