Linear matrix approximation problems AX ≈ B are often solved by the total least squares minimization (TLS). Unfortunately, the TLS solution may not exist in general. The so-called core problem theory brought an insight into this effect. Moreover, it simplified the solvability analysis if B is of column rank one by extracting a core problem having always a unique TLS solution. However, if the rank of B is larger, the core problem may stay unsolvable in the TLS sense, as shown for the first time by Hnětynková, Plešinger, and Sima (2016). Full classification of core problems with respect to their solvability is still missing. Here we fill this gap. Then we concentrate on the so-called composed (or reducible) core problems that can be represented by a composition of several smaller core problems. We analyze how the solvability class of the components influences the solvability class of the composed problem. We also show on an example that the TLS solvability class of a core problem may be in some sense improved by its composition with a suitably chosen component. The existence of irreducible problems in various solvability classes is discussed.
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We wish to thank the anonymous referee for her or his careful reading the paper and useful comments which led to improvements of our manuscript.
The research of Iveta Hnětynková has been supported by the GAČR grant No. GA17-04150J. The research of Martin Plešinger and Jana Žáková has been supported by the SGS grant of Technical University of Liberec No. 21254/2018.
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Hnětynková, I., Plešinger, M. & Žáková, J. Solvability classes for core problems in matrix total least squares minimization. Appl Math 64, 103–128 (2019). https://doi.org/10.21136/AM.2019.0252-18
- linear approximation problem
- core problem theory
- total least squares
- (ir)reducible problem