An Introduction to Linear AlgebraCourier Corporation, 3 déc. 2012 - 464 pages "The straight-forward clarity of the writing is admirable." — American Mathematical Monthly. This work provides an elementary and easily readable account of linear algebra, in which the exposition is sufficiently simple to make it equally useful to readers whose principal interests lie in the fields of physics or technology. The account is self-contained, and the reader is not assumed to have any previous knowledge of linear algebra. Although its accessibility makes it suitable for non-mathematicians, Professor Mirsky's book is nevertheless a systematic and rigorous development of the subject. Part I deals with determinants, vector spaces, matrices, linear equations, and the representation of linear operators by matrices. Part II begins with the introduction of the characteristic equation and goes on to discuss unitary matrices, linear groups, functions of matrices, and diagonal and triangular canonical forms. Part II is concerned with quadratic forms and related concepts. Applications to geometry are stressed throughout; and such topics as rotation, reduction of quadrics to principal axes, and classification of quadrics are treated in some detail. An account of most of the elementary inequalities arising in the theory of matrices is also included. Among the most valuable features of the book are the numerous examples and problems at the end of each chapter, carefully selected to clarify points made in the text. |
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Page vii
... Matrix groups and operator groups 9.3. 9.4. 9.5. Representation of groups by matrices Groups of singular matrices Invariant spaces and groups of linear transformations X. CANONICAL FORMS 10.1. The idea of a canonical form 10.2. Diagonal ...
... Matrix groups and operator groups 9.3. 9.4. 9.5. Representation of groups by matrices Groups of singular matrices Invariant spaces and groups of linear transformations X. CANONICAL FORMS 10.1. The idea of a canonical form 10.2. Diagonal ...
Page viii
... form Simultaneous similarity transformations MATRIX ANALYSIS Convergent matrix sequences Power series and matrix ... diagonal form 12.3. General reduction to diagonal form 12.4. The problem of equivalence. Rank and signature 12.5 ...
... form Simultaneous similarity transformations MATRIX ANALYSIS Convergent matrix sequences Power series and matrix ... diagonal form 12.3. General reduction to diagonal form 12.4. The problem of equivalence. Rank and signature 12.5 ...
Page 76
... form y1 = x1, y2 = :c2,..., y,, = :t',,. This is known as the identical substitution. DEFINITION 3.2.5. (i) A DIAGONAL MATRIX is a square matrix all of whose elements outside the diagonal are equal to zero. (ii) A SCALAR MATRIX is a ...
... form y1 = x1, y2 = :c2,..., y,, = :t',,. This is known as the identical substitution. DEFINITION 3.2.5. (i) A DIAGONAL MATRIX is a square matrix all of whose elements outside the diagonal are equal to zero. (ii) A SCALAR MATRIX is a ...
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algebra assertion assume automorphism basis bilinear form bilinear operator canonical forms characteristic polynomial characteristic roots characteristic vectors coefiicients commute complement complex numbers convergent coordinates Deduce defined DEFINITION denote determinant diagonal elements diagonal form diagonal matrix dimensionality E-operations edition equal EXERCISE field find finite fixed follows functions geometry Hence hermitian form hermitian matrix identity implies inequality infinite integers inverse isomorphic linear combination linear equations linear manifold linear transformation linearly independent matrix group matrix of order minimum polynomial multiplication non-singular linear transformation non-singular matrix numbers obtain orthogonal matrix permutation positive semi-definite possesses problems proof of Theorem prove quadratic form quadric rank real symmetric reduces representation represented respect result rotation satisfies scalar Show similar singular skew-symmetric matrix solution specified square matrix suppose symmetric matrix Theorem theory tions unique unit element unitary matrix values vanish variables vector space view of Theorem write zero