Description
Book SynopsisCustomarily, much of traditional mathematics curricula was predicated on ''by hand'' calculation. However, ubiquitous computing requires us to refresh what we teach and how it is taught. This is especially true in the rapidly broadening fields of Data Mining and Artificial Intelligence, and also in fields such as Bioinformatics, which all require the use of Singular Value Decomposition (SVD). Indeed, SVD is sometimes called the jewel in the crown of linear algebra.Linear Algebra for 21st Century Applications adapts linear algebra to best suit modern teaching and application, and it places the SVD as central to the text early on to empower science and engineering students to learn and use potent practical and theoretical techniques. No rigour is lost in this new route as the text demonstrates that most theory is better proved with an SVD.In addition to this, there is earlier introduction, development, and emphasis on orthogonality that is vital in so many applied disciplines throughout
Trade ReviewHighly recommended for everyone needing linear algebra competence and looking for a motivating, application oriented, comprehensible yet complete text, using modern computational tools. * Dieter Riebesehl, zbMATH Open *
this is the first text I have read that uses SVD as the main operation to solve systems of linear equations instead of the traditional augmented matrix and elementary row operations to obtain a reduced row echelon form * Peter Olszewski, Pennsylvania State University, Acta Crystallographica *
Table of Contents1: Vectors 2: Systems of linear equations 3: Matrices encode system interactions 4: Eigenvalues and eigenvectors of symmetric matrices 5: Approximate matrices 6: Determinants distinguish matrices 7: Eigenvalues and eigenvectors in general
