Linear Algebra
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- Taschenbuch
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Form:Einzelkauf Download
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Sprache:Englisch
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eBook Format:ePUB
- ePUB 3 127,00 €
- PDF 51,95 €
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55,95 €
inkl. gesetzl. MwSt.Beschreibung
Produktdetails
Format
ePUB
Kopierschutz
Nein
Family Sharing
Nein
Text-to-Speech
Ja
Erscheinungsdatum
05.03.2007
Verlag
Elsevier Science & Techn.Seitenzahl
520 (Printausgabe)
Auflage
2. Auflage
Sprache
Englisch
EAN
9780080510262
In this appealing and well-written text, Richard Bronson gives readers a substructure for a firm understanding of the abstract concepts of linear algebra and its applications. The author starts with the concrete and computational, and leads the reader to a choice of major applications (Markov chains, least-squares approximation, and solution of differential equations using Jordan normal form). The first three chapters address the basics: matrices, vector spaces, and linear transformations. The next three cover eigenvalues, Euclidean inner products, and Jordan canonical forms, offering possibilities that can be tailored to the instructor's taste and to the length of the course. Bronson's approach to computation is modern and algorithmic, and his theory is clean and straightforward. Throughout, the views of the theory presented are broad and balanced. Key material is highlighted in the text and summarized at the end of each chapter. The book also includes ample exercises with answers and hints. With its inclusion of all the needed features, this text will be a pleasure for professionals, teachers, and students.
- Introduces deductive reasoning and helps the reader develop a facility with mathematical proofs
- Gives computational algorithms for finding eigenvalues and eigenvectors
- Provides a balanced approach to computation and theory
- Superb motivation and writing
- Excellent exercise sets, ranging from drill to theoretical/challeging
- Useful and interesting applications not found in other introductory linear algebra texts
- Introduces deductive reasoning and helps the reader develop a facility with mathematical proofs
- Gives computational algorithms for finding eigenvalues and eigenvectors
- Provides a balanced approach to computation and theory
- Superb motivation and writing
- Excellent exercise sets, ranging from drill to theoretical/challeging
- Useful and interesting applications not found in other introductory linear algebra texts
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