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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... linear equations VECTOR SPACES AND LINEAR MANIFOLDS 2.1. 2.2. 2.3. 2.4. 2.5. The algebra of vectors Linear manifolds ... manifold Linear operators and their representations Isomorphisms and automorphisms of linear manifolds Further ...
... linear equations VECTOR SPACES AND LINEAR MANIFOLDS 2.1. 2.2. 2.3. 2.4. 2.5. The algebra of vectors Linear manifolds ... manifold Linear operators and their representations Isomorphisms and automorphisms of linear manifolds Further ...
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... manifold', derived by abstraction from that of a vector space, and shall study the properties of this abstract system, returning from time to time to the particular ... linear manifold and let 44 VECTOR SPACES AND LINEAR MANIFOLDS II,§2.2.
... manifold', derived by abstraction from that of a vector space, and shall study the properties of this abstract system, returning from time to time to the particular ... linear manifold and let 44 VECTOR SPACES AND LINEAR MANIFOLDS II,§2.2.
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L. Mirsky. DEFINITION 2.2.2. Let EUI be a linear manifold and let SIR' be a set of elements of EUI. If EUI' is also a linear manifold with respect to the same operations of multiplication by scalars and addition as EIR, then 'IR' is ...
L. Mirsky. DEFINITION 2.2.2. Let EUI be a linear manifold and let SIR' be a set of elements of EUI. If EUI' is also a linear manifold with respect to the same operations of multiplication by scalars and addition as EIR, then 'IR' is ...
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... manifold Elli, and let Y1,...,Y; be any elements of 'JR. Show that X1,...,Xk, Y1,...,Y; are generators of SIR. EXERCISE 2.2.5. If a linear manifold fill is spanned ... manifold, i.e. the linear 48 VECTOR SPACES AND LINEAR MANIFOLDS II,§2.2.
... manifold Elli, and let Y1,...,Y; be any elements of 'JR. Show that X1,...,Xk, Y1,...,Y; are generators of SIR. EXERCISE 2.2.5. If a linear manifold fill is spanned ... manifold, i.e. the linear 48 VECTOR SPACES AND LINEAR MANIFOLDS II,§2.2.
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... linearly dependent. DEFINITION 2.3.2. A BASIS of a linear manifold 93? is a finite ordered set of elements X1,..., X k e EUI having the property that every X e SUI is expressible as a unique linear combination of X1,..., X ,,.T Thus the ...
... linearly dependent. DEFINITION 2.3.2. A BASIS of a linear manifold 93? is a finite ordered set of elements X1,..., X k e EUI having the property that every X e SUI is expressible as a unique linear combination of X1,..., X ,,.T Thus the ...
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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