Smooth singular value decomp. of complex matrix function
                    Version 1.0.1 (5.27 KB) by  
                  Alessandro Pugliese
                
                
                  Numerical computation of a smooth singular value decomposition of a n-by-n complex matrix valued function of one real parameter
                
                  
              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
Cite As
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.
MATLAB Release Compatibility
              Created with
              R2023b
            
            
              Compatible with any release
            
          Platform Compatibility
Windows macOS LinuxTags
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