Numerical linear algebra
From Wikipedia, the free encyclopedia
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, computational finance, materials science simulations, structural biology, datamining, and 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.
[edit] See also
- Numerical analysis, of which numerical linear algebra is a subspecialty
- Gaussian elimination, the most important algorithm in numerical linear algebra
- BLAS, subroutines for numerical linear algebra on high-performance computers
[edit] References
- Leader, Jeffery J. (2004). Numerical Analysis and Scientific Computation. Addison Wesley. ISBN 0-201-73499-0.
- Trefethen, L. N., and Bau, D. III. "Numerical Linear Algebra". Society for Industrial and Applied Mathematics, 1997. ISBN 0-89871-361-7.
