Smith Linear Algebra

Erscheinungsjahr 2012
ISBN: 978-1-4615-9995-1
Verlag: Springer US
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, 280 Seiten, eBook

Reihe: Undergraduate Texts in Mathematics

This text is written for a course in linear algebra at the (U.S.) sophomore undergraduate level, preferably directly following a one-variable calculus course, so that linear algebra can be used in a course on multidimensional calculus. Realizing that students at this level have had little contact with complex numbers or abstract mathematics the book deals almost exclusively with real finite-dimensional vector spaces in a setting and formulation that permits easy generalization to abstract vector spaces. The parallel complex theory is developed in the exercises. The book has as a goal the principal axis theorem for real symmetric transformations, and a more or less direct path is followed. As a consequence there are many subjects that are not developed, and this is intentional. However a wide selection of examples of vector spaces and linear trans formations is developed, in the hope that they will serve as a testing ground for the theory. The book is meant as an introduction to linear algebra and the theory developed contains the essentials for this goal. Students with a need to learn more linear algebra can do so in a course in abstract algebra, which is the appropriate setting. Through this book they will be taken on an excursion to the algebraic/analytic zoo, and introduced to some of the animals for the first time. Further excursions can teach them more about the curious habits of some of these remarkable creatures.

Zielgruppe

Research

Autoren/Hrsg.

Smith, L.

Inhaltsverzeichnis

1 Vectors in the plane and space.- 2 Vector spaces.- 3 Subspaces.- 4 Examples of vector spaces.- 5 Linear independence and dependence.- 6 Bases and finite-dimensional vector spaces.- 7 The elements of vector spaces: a summing up.- 8 Linear transformations.- 9 Linear transformations: some numerical examples.- 10 Matrices and linear transformations.- 11 Matrices.- 12 Representing linear transformations by matrices.- 12bis More on representing linear transformations by matrices.- 13 Systems of linear equations.- 14 The elements of eigenvalue and eigenvector theory.- 15 Inner product spaces.- 16 The spectral theorem and quadratic forms.