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*Teach Your Students Both the Mathematics of Numerical Methods and the Art of Computer Programming*

**Introduction to Computational Linear Algebra** presents classroom-tested material on computational linear algebra and its application to numerical solutions of partial and ordinary differential equations. The book is designed for senior undergraduate students in mathematics and engineering as well as first-year graduate students in engineering and computational science.

The text first introduces BLAS operations of types 1, 2, and 3 adapted to a scientific computer environment, specifically MATLAB^{®}. It next covers the basic mathematical tools needed in numerical linear algebra and discusses classical material on Gauss decompositions as well as *LU* and Cholesky’s factorizations of matrices. The text then shows how to solve linear least squares problems, provides a detailed numerical treatment of the algebraic eigenvalue problem, and discusses (indirect) iterative methods to solve a system of linear equations. The final chapter illustrates how to solve discretized sparse systems of linear equations. Each chapter ends with exercises and computer projects.

*Teach Your Students Both the Mathematics of Numerical Methods and the Art of Computer Programming*

**Introduction to Computational Linear Algebra** presents classroom-tested material on computational linear algebra and its application to numerical solutions of partial and ordinary differential equations. The book is designed for senior undergraduate students in mathematics and engineering as well as first-year graduate students in engineering and computational science.

The text first introduces BLAS operations of types 1, 2, and 3 adapted to a scientific computer environment, specifically MATLAB^{®}. It next covers the basic mathematical tools needed in numerical linear algebra and discusses classical material on Gauss decompositions as well as *LU* and Cholesky’s factorizations of matrices. The text then shows how to solve linear least squares problems, provides a detailed numerical treatment of the algebraic eigenvalue problem, and discusses (indirect) iterative methods to solve a system of linear equations. The final chapter illustrates how to solve discretized sparse systems of linear equations. Each chapter ends with exercises and computer projects.

*Teach Your Students Both the Mathematics of Numerical Methods and the Art of Computer Programming*

**Introduction to Computational Linear Algebra** presents classroom-tested material on computational linear algebra and its application to numerical solutions of partial and ordinary differential equations. The book is designed for senior undergraduate students in mathematics and engineering as well as first-year graduate students in engineering and computational science.

The text first introduces BLAS operations of types 1, 2, and 3 adapted to a scientific computer environment, specifically MATLAB^{®}. It next covers the basic mathematical tools needed in numerical linear algebra and discusses classical material on Gauss decompositions as well as *LU* and Cholesky’s factorizations of matrices. The text then shows how to solve linear least squares problems, provides a detailed numerical treatment of the algebraic eigenvalue problem, and discusses (indirect) iterative methods to solve a system of linear equations. The final chapter illustrates how to solve discretized sparse systems of linear equations. Each chapter ends with exercises and computer projects.

*Teach Your Students Both the Mathematics of Numerical Methods and the Art of Computer Programming*

**Introduction to Computational Linear Algebra** presents classroom-tested material on computational linear algebra and its application to numerical solutions of partial and ordinary differential equations. The book is designed for senior undergraduate students in mathematics and engineering as well as first-year graduate students in engineering and computational science.

^{®}. It next covers the basic mathematical tools needed in numerical linear algebra and discusses classical material on Gauss decompositions as well as *LU* and Cholesky’s factorizations of matrices. The text then shows how to solve linear least squares problems, provides a detailed numerical treatment of the algebraic eigenvalue problem, and discusses (indirect) iterative methods to solve a system of linear equations. The final chapter illustrates how to solve discretized sparse systems of linear equations. Each chapter ends with exercises and computer projects.

*Teach Your Students Both the Mathematics of Numerical Methods and the Art of Computer Programming*

**Introduction to Computational Linear Algebra** presents classroom-tested material on computational linear algebra and its application to numerical solutions of partial and ordinary differential equations. The book is designed for senior undergraduate students in mathematics and engineering as well as first-year graduate students in engineering and computational science.

^{®}. It next covers the basic mathematical tools needed in numerical linear algebra and discusses classical material on Gauss decompositions as well as *LU* and Cholesky’s factorizations of matrices. The text then shows how to solve linear least squares problems, provides a detailed numerical treatment of the algebraic eigenvalue problem, and discusses (indirect) iterative methods to solve a system of linear equations. The final chapter illustrates how to solve discretized sparse systems of linear equations. Each chapter ends with exercises and computer projects.

*Teach Your Students Both the Mathematics of Numerical Methods and the Art of Computer Programming*

**Introduction to Computational Linear Algebra** presents classroom-tested material on computational linear algebra and its application to numerical solutions of partial and ordinary differential equations. The book is designed for senior undergraduate students in mathematics and engineering as well as first-year graduate students in engineering and computational science.

^{®}. It next covers the basic mathematical tools needed in numerical linear algebra and discusses classical material on Gauss decompositions as well as *LU* and Cholesky’s factorizations of matrices. The text then shows how to solve linear least squares problems, provides a detailed numerical treatment of the algebraic eigenvalue problem, and discusses (indirect) iterative methods to solve a system of linear equations. The final chapter illustrates how to solve discretized sparse systems of linear equations. Each chapter ends with exercises and computer projects.