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Ill-Conditioning and Regularization Techniques in Solutions of Linear Systems
| Content Provider | Scilit |
|---|---|
| Author | Bashier, Eihab B. M. |
| Copyright Year | 2020 |
| Description | If a small perturbation is introduced to either the coefficient matrix A or vector b , it might lead to a big change in the solution vector x . Hence, both the direct and iterative methods are not guaranteed to give accurate solution of the given linear system. This chapter is divided into two sections. The first section presents the concept of ill-conditioning in linear systems and how to use MATLAB® and Python to measure the condition numbers of matrices. In the second section, some regularization techniques are presented to stabilize the solutions of ill-conditioned systems. Book Name: Practical Numerical and Scientific Computing with MATLAB® and Python |
| Related Links | https://content.taylorfrancis.com/books/download?dac=C2018-0-91821-9&isbn=9780429021985&doi=10.1201/9780429021985-3&format=pdf |
| Ending Page | 87 |
| Page Count | 31 |
| Starting Page | 57 |
| DOI | 10.1201/9780429021985-3 |
| Language | English |
| Publisher | Informa UK Limited |
| Publisher Date | 2020-03-18 |
| Access Restriction | Open |
| Subject Keyword | Book Name: Practical Numerical and Scientific Computing with Matlab® and Python Python Matlab Perturbation Matrix Iterative Regularization Techniques Stabilize |
| Content Type | Text |
| Resource Type | Chapter |
