Smooth singular value decomp. of complex matrix function

Version 1.0.1 (5,27 ko) par Alessandro Pugliese
Numerical computation of a smooth singular value decomposition of a n-by-n complex matrix valued function of one real parameter
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Mise à jour 30 avr. 2025

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This function numerically computes the joint minimum variation (joint-MVD, see reference below) of an n-by-n complex matrix-valued function FUN of one real parameter. The singular vector matrices are unitary; the singular values are arranged in decreasing order and are assumed to be distinct and non-zero for all values of the parameter.
A typical call to complexSvdCont is:
[Tout,Uout,Sout,Vout,flag]=complexSvdCont(FUN,tspan,params)
See the script example_complexSvdCont.m for an example of how to use the function.
The command "help complexSvdCont" displays information and functionality of the software.
Please cite the references below if you use this software.
Authors: Alessandra Papini and Alessandro Pugliese

Citation pour cette source

L. Dieci, A. Pugliese, "SVD, joint-MVD, Berry phase, and generic loss of rank for a matrix valued function of 2 parameters", Linear Algebra and its Applications, Volume 700, Pages 137-157, 2024. https://doi.org/10.1016/j.laa.2024.07.021.

Compatibilité avec les versions de MATLAB
Créé avec R2023b
Compatible avec toutes les versions
Plateformes compatibles
Windows macOS Linux
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Version Publié le Notes de version
1.0.1

Fixed a typo; updated reference.
1.0.0