Linear Algebra Done RightSpringer Science & Business Media, 18 Tem 1997 - 251 sayfa This text for a second course in linear algebra is aimed at math majors and graduate students. The novel approach taken here banishes determinants to the end of the book and focuses on the central goal of linear algebra: understanding the structure of linear operators on vector spaces. The author has taken unusual care to motivate concepts and to simplify proofs. For example, the book presents--without having defined determinants--a clean proof that every linear operator on a finite-dimensional complex vector space (or an odd-dimensional real vector space) has an eigenvalue. A variety of interesting exercises in each chapter helps students understand and manipulate the objects of linear algebra. No prerequisites are assumed other than the usual demand for suitable mathematical maturity. Thus, the text starts by discussing vector spaces, linear independence, span, basis, and dimension. Students are introduced to inner-product spaces in the first half of the book and shortly thereafter to the finite-dimensional spectral theorem. This second edition includes a new section on orthogonal projections and minimization problems. The sections on self-adjoint operators, normal operators, and the spectral theorem have been rewritten. New examples and new exercises have been added, several proofs have been simplified, and hundreds of minor improvements have been made throughout the text. |
İçindekiler
Vector Spaces | 1 |
Complex Numbers | 2 |
Definition of Vector Space | 4 |
Properties of Vector Spaces | 11 |
Subspaces | 13 |
Sums and Direct Sums | 14 |
Exercises | 19 |
FiniteDimensional Vector Spaces | 21 |
Orthogonal Projections and Minimization Problems | 111 |
Linear Functionals and Adjoints | 117 |
Exercises | 122 |
Operators on InnerProduct Spaces | 127 |
SelfAdjoint and Normal Operators | 128 |
The Spectral Theorem | 132 |
Normal Operators on Real InnerProduct Spaces | 138 |
Positive Operators | 144 |
Span and Linear Independence | 22 |
Bases | 27 |
Dimension | 31 |
Exercises | 35 |
Linear Maps | 37 |
Definitions and Examples | 38 |
Null Spaces and Ranges | 41 |
The Matrix of a Linear Map | 48 |
Invertibility | 53 |
Exercises | 59 |
Polynomials | 63 |
Degree | 64 |
Complex Coefficients | 67 |
Real Coefficients | 69 |
Exercises | 73 |
Eigenvalues and Eigenvectors | 75 |
Invariant Subspaces | 76 |
Polynomials Applied to Operators | 80 |
UpperTriangular Matrices | 81 |
Diagonal Matrices | 87 |
Invariant Subspaces on Real Vector Spaces | 91 |
Exercises | 94 |
InnerProduct Spaces | 97 |
Inner Products | 98 |
Norms | 102 |
Orthonormal Bases | 106 |
Isometries | 147 |
Polar and SingularValue Decompositions | 152 |
Exercises | 158 |
Operators on Complex Sector Spaces | 163 |
Generalized Eigenvectors | 164 |
The Characteristic Polynomial | 168 |
Decomposition of an Operator | 173 |
Square Roots | 177 |
The Minimal Polynomial | 179 |
Jordan Form | 183 |
Exercises | 188 |
Operators on Real Vector Spaces | 193 |
Eigenvalues of Square Matrices | 194 |
Block UpperTriangular Matrices | 195 |
The Characteristic Polynomial | 198 |
Exercises | 210 |
Trace and Determinant | 213 |
Change of Basis | 214 |
Trace | 216 |
Determinant of an Operator | 222 |
Determinant of a Matrix | 225 |
Volume | 236 |
Exercises | 244 |
247 | |
249 | |
Diğer baskılar - Tümünü görüntüle
Sık kullanılan terimler ve kelime öbekleri
A₁ additive identity adjoint block upper-triangular matrix chapter characteristic polynomial column completing the proof complex inner-product space complex number complex vector space consisting of eigenvectors corollary corresponding decomposition defined definition denote dim null dim range dimension dimensional direct sum distinct eigenvalues eigen eigenpairs eigenvalues eigenvectors element entries equation example exists finite finite-dimensional vector space function hence holds implies injective invariant subspace invertible isometry lemma linear algebra linear map linearly independent linearly independent list list of vectors Mathematics matrix with respect minimal polynomial nilpotent nonzero vector Note null p(T null space null(T orthogonal orthonormal basis orthonormal list permutation positive integer positive operator Prove real inner-product space real numbers real vector space result scalar multiplication self-adjoint operator singular values span span(V1 spectral theorem square matrix square root surjective TEL(V trace unique V₁ verify words