Public Domain Matlab toolboxes installed at DAIMI
A number of public domain toolboxes have been installed and
tested (although not exhaustively) at DAIMI.
All of them come with one or more demos illustrating their use.
To use the toolboxes a line of the form
path(path,'path-to-toolbox');
should be inserted in the file $HOME/matlab/startup.m.
This adds the toolbox to the Matlab search path. It also makes
on-line help for the routines of the toolbox available via the commands
help and helpwin. To see the available help
items by, run help without any arguments. The relevant
commands are listed is listed after each of the descriptions below.
Links to any accompanying documentation, e.g. in the form of
postscript documents, are provided below.
-
Regularization Tools Version 3.0:
A Matlab package for analysis and solution of discrete
ill-posed problems, developed by Prof. Per Christian Hansen,
Dept. of Mathematical Modelling, Technical Univ. of Denmark.
Line to insert in $HOME/matlab/startup.m:
path(path,'/users/kursus/toolbox/regutools');
Click here to read the manual.
-
Rank-Revealing decompositions:
A small Matlab package is provided for computations with
rank-revealing QR decompositions.
Line to insert in $HOME/matlab/startup.m:
path(path,'/users/kursus/toolbox/rrqr');
-
Algorithms & Data Structures:
"It implements functions to create and
destroy singly and doubly linked list, stack, queue, binary tree
and red-black (balanced) binary tree. Data elements can be
inserted, deleted or searched for. A graphical representation of
trees can be shown."
Line to insert in $HOME/matlab/startup.m:
path(path,'/users/kursus/toolbox/dsatbx');
-
Statistics Toolbox: "Various statistics functions -
Distribution functions, Logistic regression,
Resampling methods, Tests, confidence intervals and
model estimation, Graphics."
Line to insert in $HOME/matlab/startup.m:
path(path,'/users/kursus/toolbox/stixbox');
- Visualization:
"PhiVis is Probabilistic Hierarchical Interactive Visualization.
It is a toolbox of MATLAB functions for visual analysis of
multivariate continuous data. It is powerful in that it
generates and links multiple projections of datasets with
potentially complex structure, but is also statistically
principled, being based on hierarchical mixtures of latent
variable Gaussian density models."
Lines to insert in $HOME/matlab/startup.m:
path(path,'/users/kursus/toolbox/PhiVis/lib');
path(path,'/users/kursus/toolbox/PhiVis/tutorial');
Click here
to read the documentation.
- Neural Networks:
"The Netlab simulation software is designed to provide the central
tools necessary for the simulation of theoretically well founded
neural network algorithms for use in teaching, research
and applications development."
Line to insert in $HOME/matlab/startup.m:
path(path,'/users/kursus/toolbox/netlab');
Netlab comes with browsable documentation.
- Genetic Algorithm Optimization Toolbox:
"GAOT implements simulated evolution in the Matlab environment using
both binary and real representations. (Ordered base representation
is in the debugging stage.) This implementation is very flexible in
the genetic operators, selection functions, termination functions as
well as the evaluation functions that can be used."
Line to insert in $HOME/matlab/startup.m:
path(path,'/users/kursus/toolbox/GAOT');
Click here
to read the documentation.
A list of the avalable functions is available
here.
- Independent Component Analysis:
"The FastICA package is a public-domain MATLAB program
that implements the fast fixed-point algorithm for
independent component analysis and projection pursuit. It features an
easy-to-use graphical user interface, and a computationally powerful
algorithm."
Line to insert in $HOME/matlab/startup.m:
path(path,'/users/kursus/toolbox/fastica5');
Click here
to read the documentation.
-
Other Matlab Toolboxes on the web. A list of freeware
toolboxes. Many different applications: Statistics, Genetic
Algorithms, Neural Networks, Distributed and Parallel
applications. Just remember: "Anything free comes with no
guarantee."
Last modified April 27 1998 by Rasmus Munk Larsen /
rmunk@daimi.aau.dk