INTLAB (INTerval LABoratory) is an interval arithmetic library[1][2][3][4] using MATLAB and GNU Octave, available in Windows and Linux, macOS. It was developed by S.M. Rump from Hamburg University of Technology. INTLAB was used to develop other MATLAB-based libraries such as VERSOFT[5] and INTSOLVER,[6] and it was used to solve some problems in the Hundred-dollar, Hundred-digit Challenge problems.[7]

INTLAB (Interval Laboratory)
Original author(s)S.M. Rump
Developer(s)S.M. Rump
Cleve Moler
Shinichi Oishi etc.
Written inMATLAB/GNU Octave
Operating systemUnix, Microsoft Windows, macOS
Available inEnglish
TypeValidated numerics
Computer-assisted proof
Interval arithmetic
Affine arithmetic
Numerical linear algebra
root-finding algorithm
Numerical integration
Automatic differentiation
Numerical methods for ordinary differential equations
Websitewww.tuhh.de/ti3/intlab/

Version history

Functionality

INTLAB can help users to solve the following mathematical/numerical problems with interval arithmetic.

Works cited by INTLAB

INTLAB is based on the previous studies of the main author, including his works with co-authors.

External links

See also

References

  1. ^ a b c d e f g h i S.M. Rump: INTLAB – INTerval LABoratory. In Tibor Csendes, editor, Developments in Reliable Computing, pages 77–104. Kluwer Academic Publishers, Dordrecht, 1999.
  2. ^ a b Moore, R. E., Kearfott, R. B., & Cloud, M. J. (2009). Introduction to Interval Analysis. Society for Industrial and Applied Mathematics.
  3. ^ a b c d e f g Rump, S. M. (2010). Verification methods: Rigorous results using floating-point arithmetic. Acta Numerica, 19, 287–449.
  4. ^ a b c d Hargreaves, G. I. (2002). Interval analysis in MATLAB. Numerical Algorithms, (2009.1).
  5. ^ Rohn, J. (2009). VERSOFT: verification software in MATLAB/INTLAB.
  6. ^ Montanher, T. M. (2009). Intsolver: An interval based toolbox for global optimization. Version 1.0.
  7. ^ Bornemann, F., Laurie, D., & Wagon, S. (2004). The SIAM 100-digit challenge: a study in high-accuracy numerical computing. Society for Industrial and Applied Mathematics.
  8. ^ S. M. Rump: Verffication of positive definiteness, BIT Numerical Mathematics, 46 (2006), 433–452.
  9. ^ S.M. Rump, M. Kashiwagi: Implementation and improvements of affine arithmetic, Nonlinear Theory and Its Applications (NOLTA), IEICE, 2015.
  10. ^ Lohner, R. J. (1987). Enclosing the solutions of ordinary initial and boundary value problems. Computer arithmetic, 225–286.
  11. ^ L.B. Rall: Automatic Differentiation: Techniques and Applications, Lecture Notes in Computer Science 120, Springer, 1981.
  12. ^ S.M. Rump. Verified sharp bounds for the real gamma function over the entire floating-point range. Nonlinear Theory and Its Applications (NOLTA), IEICE, Vol.E5-N, No. 3, July, 2014.
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