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Elementary Linear Algebra (1970)

af Bernard Kolman, David R. Hill (Forfatter)

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This book presents the basic ideas of linear algebra in a manner that users will find understandable. It offers a fine balance between abstraction/theory and computational skills, and gives readers an excellent opportunity to learn how to handle abstract concepts. Included in this comprehensive and easy-to-follow manual are these topics: linear equations and matrices; solving linear systems; real vector spaces; inner product spaces; linear transformations and matrices; determinants; eigenvalues and eigenvectors; differential equations; and MATLAB for linear algebra. Because this book gives real applications for linear algebraic basic ideas and computational techniques, it is useful as a reference work for mathematicians and those in field of computer science.… (mere)
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This book is trash, using any of the free linear algebra textbook pdfs available online would be better than trying to learn anything from it. ( )
  joiewu | Mar 21, 2022 |
I was a TA for linear algebra this semester, and this was the assigned book. As always, for engineers this book is written way too much for mathematicians. The examples were lacking and there were definite typos, that I found very misleading and confusing at times when trying to teach fundamental topics. I've never found a solid linear algebra book I've liked. ( )
1 stem lemontwist | Dec 8, 2011 |
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Preface -- Linear algebra continues to be an important course for a diverse number of students for at least two reasons. First, few subjects can claim to have such widespread applications in other areas of mathematics -- multivariable calculus, differential equations, and probability, for example -- as well as physics, biology, chemistry, economics, finance, psychology, sociology, and all fields of engineering. Second, the subject presents the student at the sophomore level with an excellent opportunity to learn how to handle abstract concepts.
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This book presents the basic ideas of linear algebra in a manner that users will find understandable. It offers a fine balance between abstraction/theory and computational skills, and gives readers an excellent opportunity to learn how to handle abstract concepts. Included in this comprehensive and easy-to-follow manual are these topics: linear equations and matrices; solving linear systems; real vector spaces; inner product spaces; linear transformations and matrices; determinants; eigenvalues and eigenvectors; differential equations; and MATLAB for linear algebra. Because this book gives real applications for linear algebraic basic ideas and computational techniques, it is useful as a reference work for mathematicians and those in field of computer science.

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