Ford, W. (2015) Numerical Linear Algebra with Applications: Using MATLAB. Academic Press, London. has been cited by the following article: TITLE: Carleman Linearization and Systems of Arbitrary Depth ...

The set consists of 5 questions, with a focus on MATLAB coding tasks. Topics include solving linear systems and matrix inverses, understanding the Thomas Algorithm for tridiagonal systems, and ...

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Another benefit of using sparse matrices is that they can speed up some numerical linear algebra operations, such as solving linear systems, eigenvalue problems, or singular value decomposition.

This is in the flavour of MatLab. For those interested in using linear algebra in a symbolic setting, or for working with matrices over the integers or rational numbers (not float point numbers) ...