software.jemdoc

# jemdoc: menu{MENU}{software.html}
# jemdoc: eqs, eqsize{150}, 
# jemdoc: addpackage{amsmath}
# jemdoc: addpackage{mathdots}
# jemdoc: addpackage{amsfonts}
# jemdoc: addpackage{times}
# jemdoc: addpackage{mathptmx}
# jemdoc: showsource
= Software produced by the SLRA project

~~~
{}{img_left}{software-logo.png}{}{120px}{}{}
== [software-slra.html SLRA: Software for weighted structured low-rank approximation]
A software package is presented that computes locally optimal solutions to low-rank approximation problems with the following features:
 - constraint on the approximating matrix,
 - /weighted 2-norm/ approximation criterion,
 - /fixed elements/ in the approximating matrix,
 - /missing elements/ in the data matrix, and
 - /linear constraints/ on an approximating matrix's left kernel basis.

~~~

~~~
{}{img_left}{software-logo.png}{}{120px}{}{}
== [software-ident.html IDENT: Package for identification in behavioural setting]
An identification problem with no a priori separation of the variables into inputs and outputs and representation invariant approximation criterion is considered. The model class consists of linear time-invariant systems of bounded complexity and the approximation criterion is the minimum of a weighted 2-norm distance between the given time series and a time series that is consistent with the model. The problem is equivalent to and is solved as a mosaic-Hankel structured low-rank approximation problem. Software implementing the approach is developed and tested on benchmark problems. Additional nonstandard features of the software are specification of exact and missing variables and identification from multiple experiments.
~~~