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Numerical linear algebra

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Title: Numerical linear algebra  
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Subject: Linear algebra, Gauss–Seidel method, Jacobi method, Successive over-relaxation, Convergent matrix
Collection: Numerical Linear Algebra
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Numerical linear algebra

Numerical linear algebra is the study of algorithms for performing linear algebra computations, most notably matrix operations, on computers. It is often a fundamental part of engineering and computational science problems, such as image and signal processing, telecommunication, computational finance, materials science simulations, structural biology, data mining, bioinformatics, fluid dynamics, and many other areas. Such software relies heavily on the development, analysis, and implementation of state-of-the-art algorithms for solving various numerical linear algebra problems, in large part because of the role of matrices in finite difference and finite element methods.

Common problems in numerical linear algebra include computing the following: LU decomposition, QR decomposition, singular value decomposition, eigenvalues.

See also

References

  • J. H. Wilkinson and C. Reinsch, "Linear Algebra, volume II of Handbook for Automatic Computation" SIAM Review 14, 658 (1972).
  • Golub, Gene H.; van Loan, Charles F. (1996), Matrix Computations, 3rd edition, Johns Hopkins University Press, ISBN 978-0-8018-5414-9

External links

  • Freely available software for numerical algebra on the web, composed by Jack Dongarra and Hatem Ltaief, University of Tennessee
  • NAG Library of numerical linear algebra routines
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