The linear algebra survival guide : illustrated with mathematica /

The Linear Algebra Survival Guide offers a concise introduction to the difficult core topics of linear algebra, guiding you through the powerful graphic displays and visualization of Mathematica that make the most abstract theories seem simple - allowing you to tackle realistic problems using simple...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Szabo, Fred (Autor)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Amsterdam : Elsevier, [2015]
Temas:
Algebras, Linear.
Alg�ebre lin�eaire.
MATHEMATICS > Algebra > Intermediate.
Algebras, Linear
Lineare Algebra
Acceso en línea:Texto completo
Tabla de Contenidos:
  • Front Cover
  • The Linear Algebra Survival Guide: Illustrated with Mathematica
  • Copyright
  • About the Matrix Plot
  • Table of Contents
  • Preface
  • Dedication
  • About the Author
  • Introduction
  • Chapter 1: A
  • Addition of Matrices
  • Adjacency Matrix
  • Adjoint Matrix
  • Adjoint Transformation
  • Adjugate of a Matrix
  • Affine Transformation
  • Algebraic Multiplicity of an Eigenvalue
  • Angle
  • Area of a Parallelogram
  • Area of a Triangle
  • Array
  • Arrow
  • Augmented Matrix
  • Chapter 2: B
  • Back Substitution
  • Band Matrix
  • Basic Variable of a Linear System
  • Basis of a Vector Space
  • Bijective Linear Transformation
  • Bilinear Functional
  • Chapter 3: C
  • Cartesian Product of Vector Spaces
  • Cauchy-Schwarz Inequality
  • Cayley-Hamilton Theorem
  • Change-of-Basis Matrix
  • Characteristic Polynomial
  • Cholesky Decomposition
  • Codimension of a Vector Subspace
  • Codomain of a Linear Transformation
  • Cofactor Matrix
  • Column Space
  • Column Vector
  • Companion Matrix
  • Complex Conjugate
  • Composition of Linear Transformations
  • Condition Number of a Matrix
  • Congruence Transformation
  • Congruent Symmetric Matrices
  • Conjugate Transpose
  • Consistent Linear System
  • Contraction Along a Coordinate Axis
  • Coordinate Conversion Matrix
  • Coordinate System
  • Coordinate Vector
  • Correlation Coefficient
  • Correlation Matrix
  • Cosine of an Angle
  • Covariance
  • Covariance Matrix
  • Cramer's Rule
  • Cross Product
  • Chapter 4: D
  • Defective Matrix
  • Determinant
  • Diagonal
  • Diagonal Decomposition
  • Diagonal Matrix
  • Diagonal of a Matrix
  • Difference Equation
  • Dimension of a Vector Space
  • Dimensions of a Matrix
  • Dirac Matrix
  • Direct Sum of Vector Spaces
  • Discrete Fourier Transform.
  • Discriminant of a Hessian Matrix
  • Disjoint Subspaces
  • Distance Between a Point and a Plane
  • Distance Function
  • Domain of a Linear Transformation
  • Dot Product
  • Dual Space
  • Chapter 5: E
  • Echelon Form
  • Eigenspace
  • Eigenvalue
  • Eigenvector
  • Elementary Matrix
  • Elementary Row Operation
  • Euclidean Distance
  • Euclidean Norm
  • Euclidean Space
  • Exact Solution
  • Expansion Along a Coordinate Axis
  • Exponential Form of Complex Numbers
  • Chapter 6: F
  • Finite-Dimensional Vector Space
  • Forward Substitution
  • Fourier Matrix
  • Fourier Transform
  • Fredholm's Theorem
  • Free Variable of a Linear System
  • Frobenius Companion Matrix
  • Frobenius Norm
  • Full Rank of a Matrix
  • Fundamental Subspace
  • Fundamental Theorem of Algebra
  • Chapter 7: G
  • Gaussian Elimination
  • Gauss-Jordan Elimination
  • General Solution of a Linear System
  • Geometric Multiplicity of an Eigenvalue
  • Geometric Transformation
  • Gram-Schmidt Process
  • Chapter 8: H
  • Hankel Matrix
  • Height of a Column Vector
  • Hermitian Inner Product
  • Hermitian Matrix
  • Hessenberg Matrix
  • Hessian Matrix
  • Hilbert Matrix
  • Homogeneous Coordinate
  • Homogeneous Linear System
  • Householder Matrix
  • Chapter 9: I
  • Identity Matrix
  • Ill-Conditioned Matrix
  • Image of a Linear Transformation
  • Incidence Matrix
  • Inconsistent Linear System
  • Injective Linear Transformation
  • Inner Product
  • Inner Product Norm
  • Inner Product Space
  • Interpolating Polynomial
  • Intersection of Subspaces
  • Invariant Subspace
  • Inverse of a Linear Transformation
  • Inverse of a Matrix
  • Invertible Matrix
  • Isometry
  • Isomorphism of Vector Spaces
  • Chapter 10: J
  • Jacobian Determinant
  • Jordan Block
  • Jordan Matrix
  • Chapter 11: K.
  • Kernel of a Linear Transformation
  • Kronecker Delta
  • Kronecker Product
  • Chapter 12: L
  • Law of Cosines
  • Least Squares
  • Left Null Space
  • Length of a Vector
  • Linear Combination
  • Linear Dependence
  • Linear Dependence Relation
  • Linear Equation
  • Linear Independence
  • Linear Operator
  • Linear System
  • Linear Transformation
  • Lower-Triangular Matrix
  • LU Decomposition
  • Chapter 13: M
  • Manhattan Distance
  • Markov Matrix
  • Mathematica Domain of a Scalar
  • Matrix
  • Matrix Addition
  • Matrix Decomposition
  • Matrix Equation
  • Matrix Norm
  • Matrix Space
  • Matrix-Vector Product
  • Minimal Polynomial
  • Minor Matrix
  • Multiplication of Matrices
  • Chapter 14: N
  • Norm
  • Normal Basis of a Vector Space
  • Normal Equation
  • Normal Matrix
  • Normal to a Plane
  • Normalization of a Matrix Equation
  • Normalization of a Vector
  • Normed Vector Space
  • Null Space
  • Nullity of a Matrix
  • Chapter 15: O
  • Orthogonal Basis
  • Orthogonal Complement
  • Orthogonal Decomposition
  • Orthogonal Matrix
  • Orthogonal Projection
  • Orthogonal Transformation
  • Orthogonal Vectors
  • Orthogonality
  • Orthogonalization
  • Orthonormal Basis
  • Overdetermined Linear System
  • Chapter 16: P
  • Particular Solution of a Linear System
  • Pauli Spin Matrix
  • Perfectly Conditioned Matrix
  • Permutation Matrix
  • Pivot Column of a Matrix
  • Plane in Euclidean Space
  • Polar Form of a Complex Number
  • Polynomial Space
  • Positive-Definite Matrix
  • Principal Axis Theorem
  • Product of Two Vector Spaces
  • Pseudoinverse of a Matrix
  • Pythagorean Theorem
  • Chapter 17: Q
  • QR Decomposition
  • Quadratic Form
  • Quintic Polynomial
  • Chapter 18: R
  • Random Matrix
  • Range of a Linear Transformation
  • Rank-Deficient Matrix
  • Rank-Nullity Theorem
  • Rank of a Matrix.
  • Rational Canonical Form
  • Rayleigh Quotient
  • Rectangular Matrix
  • Reduced Row Echelon Matrix
  • Reflection
  • Roots of Unity
  • Rotation
  • Row Echelon Matrix
  • Row-Equivalent Matrices
  • Row Space
  • Row Vector
  • Chapter 19: S
  • Scalar
  • Scalar Multiple of a Matrix
  • Scalar Multiplication
  • Scalar Triple Product
  • Scaling
  • Schur Decomposition
  • Self-Adjoint Transformation
  • Shear
  • Sigma Notation
  • Similar Matrices
  • Similarity Matrix
  • Similarity Transformation
  • Singular Matrix
  • Singular Value
  • Singular Value Decomposition
  • Singular Vector
  • Skew Symmetric Matrix
  • Solution of a Linear System
  • Span of a List of Vectors
  • Sparse Matrix
  • Spectral Decomposition
  • Spectral Theorem
  • Square Matrix
  • Standard Basis
  • Standard Deviation of a Numerical Vector
  • Stochastic Matrix
  • Subdiagonal of a Matrix
  • Submatrix
  • Subspace
  • Sum of Subspaces
  • Superdiagonal of a Matrix
  • Surjective Linear Transformation
  • Sylvester's Theorem
  • Symmetric Matrix
  • System of Linear Equations
  • Chapter 20: T
  • Toeplitz Matrix
  • Trace
  • Transformation
  • Transformational Geometry
  • Transition Matrix
  • Translation
  • Transpose of a Matrix
  • Triangle Inequality
  • Triangular Matrix
  • Chapter 21: U
  • Underdetermined Linear System
  • Unit Circle
  • Unit Vector
  • Unitary Matrix
  • Upper-Triangular Matrix
  • Chapter 22: V
  • Vandermonde Matrix
  • Variance of a Vector
  • Vector
  • Vector Addition
  • Vector Component
  • Vector Cross Product
  • Vector Norm
  • Vector Spaces
  • Vector Triple Product
  • Volume of a Parallelepiped
  • Chapter 23: W
  • Well-Conditioned Matrix
  • Wronskian
  • Chapter 24: Z
  • Zero Matrix
  • Zero Space
  • Zero Vector
  • Index.

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