Jordan Canonical Form
theory and practice
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Author
Publication
2009 - Morgan & Claypool Publishers, San Rafael, Calif. (1537 Fourth Street, San Rafael, CA 94901 USA), California
Language
English
Word Count
24,000 words, Guess
Page Count
96 pages
Physical Format
Electronic resource
Identifiers
- Internet Archivejordancanonicalf00wein
- Internet Archivejordancanonicalf00wein_427
- ISBN-139781608452514
- ISBN-139781608452507
- ISBN-101608452514
and 5 more
- ISBN-101608452506
- OCLC Control Number463284175
- Better World Books9781608452507
- Better World Books9781608452514
- Open LibraryOL25543111M
Classifications
- DDC512.24
- LCCQA252.5 .W455 2009
Alternate Titles
- Synthesis digital library of engineering and computer science.
Description
Jordan Canonical Form (JCF) is one of the most important, and useful, concepts in linear algebra. The JCF of a linear transformation, or of a matrix, encodes all of the structural information about that linear transformation, or matrix. This book is a careful development of JCF. After beginning with background material, we introduce Jordan Canonical Form and related notions: eigenvalues, (generalized) eigenvectors, and the characteristic and minimum polynomials.We decide the question of diagonalizability, and prove the Cayley-Hamilton theorem. Then we present a careful and complete proof of the fundamental theorem: Let V be a finite-dimensional vector space over the field of complex numbers C, and let T : V -. V be a linear transformation. Then T has a Jordan Canonical Form. This theorem has an equivalent statement in terms of matrices: Let A be a square matrix with complex entries. Then A is similar to a matrix J in Jordan Canonical Form, i.e., there is an invertible matrix P and a matrix J in Jordan Canonical Form with A = PJP-1.We further present an algorithm to find P and J , assuming that one can factor the characteristic polynomial of A. In developing this algorithm we introduce the eigenstructure picture (ESP) of a matrix, a pictorial representation that makes JCF clear. The ESP of A determines J , and a refinement, the labelled eigenstructure picture (ESP) of A, determines P as well.We illustrate this algorithm with copious examples, and provide numerous exercises for the reader.
Subjects
Series Statement
- Synthesis lectures on mathematics and statistics -- # 6
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