INTLAB

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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]

Contents

INTLAB (Interval Laboratory)
Original author(s) S.M. Rump
Developer(s) S.M. Rump
Cleve Moler
Shinichi Oishi etc.
Written in MATLAB/GNU Octave
Operating system Unix, Microsoft Windows, macOS
Available in English
Type Validated numerics
Computer-assisted proof
Interval arithmetic
Affine arithmetic
Numerical linear algebra
root-finding algorithm
Numerical integration
Automatic differentiation
Numerical methods for ordinary differential equations
Website www.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.

See also

Related Research Articles

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References

  1. 1 2 3 4 5 6 7 8 9 S.M. Rump: INTLAB – INTerval LABoratory. In Tibor Csendes, editor, Developments in Reliable Computing, pages 77–104. Kluwer Academic Publishers, Dordrecht, 1999.
  2. 1 2 Moore, R. E., Kearfott, R. B., & Cloud, M. J. (2009). Introduction to Interval Analysis. Society for Industrial and Applied Mathematics.
  3. 1 2 3 4 5 6 7 Rump, S. M. (2010). Verification methods: Rigorous results using floating-point arithmetic. Acta Numerica, 19, 287–449.
  4. 1 2 3 4 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.