Linear Algebra: Theory And Applications

This is a book on linear algebra and matrix theory. While it is self contained, it will work best for those who have already had some exposure to linear algebra. It is also assumed that the reader has had calculus. Some optional topics require more analysis than this, however.

This book combines a solid theoretical background in linear algebra with practical algorithms for numerical solution of linear algebra problems.

This book combines a solid theoretical background in linear algebra with practical algorithms for numerical solution of linear algebra problems. Developed from a number of courses taught repeatedly by the authors, the material covers topics like matrix algebra, theory for linear systems of equations, spectral theory, vector and matrix norms combined with main direct and iterative numerical methods, least squares problems, and eigenproblems.

This book combines a solid theoretical background in linear algebra with practical algorithms for numerical solution of linear algebra problems. Developed from a num-ber of courses taught repeatedly by the authors, the material covers topics like matrix algebra, theory for linear systems of equations, spectral theory, vector and matrix normscombined with main direct and iterative numerical methods, least squares problems, and eigenproblems.

Learn concepts in linear algebra and matrix analysis, and implement them in MATLAB and Python.

Learn concepts in linear algebra and matrix analysis, and implement them in MATLAB and Python.