There are a number of demo files for the different INTLAB toolboxes.
view the demos directly, or copy the
demos directory file
into your working directory, change your directory by "cd demos" and
INTLAB has several thousand users in more than 50 countries and more
than 1500 citations in scientific publications.
INTLAB is used in many areas, from verification of chaos to population
biology, from controller design to computer-assisted proofs,
from PDEs to Petri Nets
some selected Refences to INTLAB).
Over the years
helped to improve INTLAB, my dearest thanks to them!
The main focus of INTLAB is to produce reliable results. Any result is
proved to be true under any circumstances, in particular covering rounding
errors and all error terms. The other main focus is to be fast.
The philosophy of INTLAB is that everything is written in Matlab code
to assure best portability. Interval vector and matrix operations are very
fast due to extensive use of BLAS routines. However, nonlinear
computations and loops may slow down the system significantly due to
interpretation overhead and extensive use of the operator concept.
Details and examples about timing can be found
Moreover, some routines treat extremely ill-conditioned problems.
Details and examples are
Principle of verified numerical computations by S. Oishi et al., Corona publisher, Japan
An elementary introduction can be found in Gleitkommaarithmetik auf
dem Prüfstand [Wie werden verifiziert(e) numerische Lösungen
berechnet?]. Jahresbericht der Deutschen Mathematiker-Vereinigung,
118(3):179-226, 2016. [written in German]
Hargreaves' thesis (supervisor Nicholas J. Higham)
Interval Analysis in Matlab
is a nice introduction into parts of INTLAB together with a tutorial. Moreover,
some routines written by Hargreaves in INTLAB are presented, among them
an algorithm to find all zeros of a nonlinear function within a box and
a computation of Viswanath's constant, the common limit of random
Tiago Montanher wrote
INTSOLVER, an INTLAB based solver for
A large collection of verification algorithms written in Matlab/INTLAB
Most routines in INTLAB are self-explaining and/or information can be
obtained by the Matlab/Octave help command (cf. also readme.txt for
For download and installation under Octave see
here. Disclaimer: Few routines are not supported by Octave, in
particular concerning graphics.
If you use INTLAB in publications, please include the reference
S.M. Rump: INTLAB - INTerval LABoratory. In Tibor Csendes, editor,
Developments in Reliable Computing, pages 77-104. Kluwer Academic
Publishers, Dordrecht, 1999.
INTLAB is thoroughly tested under Windows, Linux and MacOS operating system.
It runs under most Matlab versions including R2022a.
The parallel toolbox of Matlab applies only to a limited subset of
Matlab utilities, therefore the parfor command and alike do not work
with INTLAB. However, several incarnations of Matlab/INTLAB may run
INTLAB LICENSE INFORMATION
Copyright (c) 1998 - 2023 Siegfried M. Rump @ TUHH,
Institute for Reliable Computing
All rights reserved.
===> INTLAB can be downloaded and used for private and for purely
academic purposes, and for commercial purposes within a company.
In any case proper reference has to be given acknowledging that the
software package INTLAB has been developed by
Siegfried M. Rump at Hamburg University of Technology, Germany.
===> The use of INTLAB in a commercial product which needs INTLAB
or parts of INTLAB to work properly requires a special license.
This is independent of whether the commercial product is used privately
or for commercial purposes. To obtain such a license contact the author
Siegfried M. Rump (@tuhh.de).
===> Neither the name of the university nor the name of the author
may be used to endorse or promote products derived with or from
this software without specific prior written permission.
THIS SOFTWARE IS PROVIDED AS IS AND WITHOUT ANY EXPRESS OR IMPLIED WARRANTIES,
INCLUDING, WITHOUT LIMITATIONS, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND
FITNESS FOR A PARTICULAR PURPOSE.
DISCLAIMER: Extensive tests have been performed to ensure reliability
of the algorithms. However, neither an error-free processor nor an
error-free program can be guaranteed.
Prof. Dr. Siegfried M. Rump
Institute for Reliable Computing
Hamburg University of Technology
Am Schwarzenberg-Campus 3