Abstract
In applied sciences, one is quite often led to face a linear system of the form
, where A is a square matrix of dimension \(n\times n\) whose elements aij are either real or complex, while x and b are column vectors of dimension n: x represents the unknown solution while b is a given vector.
Keywords
- Iterative Method
- Cholesky Factorization
- Preconditioned Conjugate Gradient
- Iteration Matrix
- Jacobi Method
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
Author information
Authors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer-Verlag Berlin Heidelberg
About this chapter
Cite this chapter
Quarteroni, A., Saleri, F., Gervasio, P. (2014). Linear systems. In: Scientific Computing with MATLAB and Octave. Texts in Computational Science and Engineering, vol 2. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-45367-0_5
Download citation
DOI: https://doi.org/10.1007/978-3-642-45367-0_5
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-45366-3
Online ISBN: 978-3-642-45367-0
eBook Packages: Mathematics and StatisticsMathematics and Statistics (R0)