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  • 全新线代数导引金小庆//刘伟辉//刘璇//赵志9787030721631
  • 正版
    • 作者: 金小庆//刘伟辉//刘璇//赵志著 | 金小庆//刘伟辉//刘璇//赵志编 | 金小庆//刘伟辉//刘璇//赵志译 | 金小庆//刘伟辉//刘璇//赵志绘
    • 出版社: 科学出版社
    • 出版时间:2022-01-01
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    • 作者: 金小庆//刘伟辉//刘璇//赵志著| 金小庆//刘伟辉//刘璇//赵志编| 金小庆//刘伟辉//刘璇//赵志译| 金小庆//刘伟辉//刘璇//赵志绘
    • 出版社:科学出版社
    • 出版时间:2022-01-01
    • 版次:1
    • 印次:1
    • 字数:300000
    • 页数:221
    • 开本:16开
    • ISBN:9787030721631
    • 版权提供:科学出版社
    • 作者:金小庆//刘伟辉//刘璇//赵志
    • 著:金小庆//刘伟辉//刘璇//赵志
    • 装帧:平装
    • 印次:1
    • 定价:78.00
    • ISBN:9787030721631
    • 出版社:科学出版社
    • 开本:16开
    • 印刷时间:暂无
    • 语种:暂无
    • 出版时间:2022-01-01
    • 页数:221
    • 外部编号:1202724247
    • 版次:1
    • 成品尺寸:暂无

    Chapter 1 Linear Systems and Matrices
    1.1 Introduction to Linear Systems and Matrices
    1.1.1 Linear equations and linear systems
    1.1.2 Matrices
    1.1.3 Elementary row oraios
    1.2 Gauss-Jordan Elimination
    1.2.1 Reduced row-echelon form
    1.2.2 Gauss-Jordan elimination
    1.. Homogeneous linear systems
    1.3 Matrix Oraios
    1.3.1 Oraios on matrices
    1.3.2 Partition of matrices
    1.3.3 Matrix product by columns and by rows
    1.3.4 Matrix product of partitioned matrices
    1.3.5 Matrix form of a linear system
    1.3.6 Transpose and trace of a matrix
    1.4 Rules of Matrix Oraios and Inverses
    1.4.1 Basic properties of matrix oraios
    1.4.2 Identity matrix and zero matrix
    1.4.3 Inverse of a matrix
    1.4.4 Powers of a matrix
    1.5 Elementary Matrices and a Method for Finding A-1
    1.5.1 Elementary matrices and their properties
    1.5.2 Main theorem of invertibility
    1.5.3 A method for finding A-1
    1.6 Further Results on Systems and Invertibility
    1.6.1 A basic theorem
    1.6.2 Properties of invertible matrices
    1.7 Some Special Matrices
    1.7.1 Diagonal and triangular matrices
    1.7.2 Symmetric matrix
    Exercises
    Chapter 2 Determinants
    2.1 Determinant Function
    2.1.1 Permutation, inversion, and elementary product
    2.1.2 Definition of determinant function
    2.2 Evaluation of Determinants
    2.2.1 Elementary theorems
    2.2.2 A method for evaluating determinants
    . Properties of Determinants
    ..1 Basic properties
    ..2 Determinant of a matrix product
    .. Summary
    2.4 Cofactor Expansions an Caer’s Rule
    2.4.1 Cofactors
    2.4.2 Cofactor expansions
    2.4.3 Adjoint of a matrix
    2.4.4 Cramer’s rule
    Exercises
    Chapter 3 Euclidean Vector Spaces
    3.1 Euclidean n-Space
    3.1.1 n-vector space
    3.1.2 Euclidean n-space
    3.1.3 Norm, distance, angle, and orthogonality
    3.1.4 Some remarks
    3.2 Linear Transformations from Rn to Rm
    3.2.1 Linear transformations from Rn to Rm
    3.2.2 Some important linear transformations
    3.. Coitions of linear transformations
    3.3 Properties of Transformations
    3.3.1 Linearity conditions
    3.3.2 Example
    3.3.3 One-to-one transformations
    3.3.4 Summary
    Exercises
    Chapter 4 General Vector Spaces
    4.1 Real Vector Spaces
    4.1.1 Vector space axioms
    4.1.2 Some properties
    4.2 Subspaces
    4.2.1 Definition of subspace
    4.2.2 Linear combinations
    4.3 Linear Independence
    4.3.1 Linear independence and linear dependence
    4.3.2 Some theorems
    4.4 Basis and Dimension
    4.4.1 Basis for vector space
    4.4.2 Coordinates
    4.4.3 Dimension
    4.4.4 Some fundamental theorems
    4.4.5 Dimension theorem for subspaces
    4.5 Row Space, Column Space, and Nullspace
    4.5.1 Definition of row space, column space, and nullspace
    4.5.2 Relation between solutions of Ax = 0 and Ax=b
    4.5.3 Bases for three spaces
    4.5.4 A procedure for finding a basis for span(S)
    4.6 Rank an Nlty
    4.6.1 Rank an nlty
    4.6.2 Rank for matrix oraios
    4.6.3 Consistency theorems
    4.6.4 Summary
    Exercises
    Chapter 5 Inner Product Spaces
    5.1 Inner Products
    5.1.1 General inner products
    5.1.2 Examples
    5.2 Angle and Orthogonality
    5.2.1 Angle between two vectors and orthogonality
    5.2.2 Properties o enth, distance, and orthogonality
    5.. Complement
    5.3 Orthogonal Bases an Ga-Schmidrces
    5.3.1 Orthogonal and orthonormal bases
    5.3.2 Projection theorem
    5.3.3 Gram-Schmidt process
    5.3.4 R-decoition
    5.4 Best Approximation and Least Squares
    5.4.1 Orthogonal projections viewed as approximations
    5.4.2 Least squares solutions of linear systems
    5.4.3 Uniqueness of least squares solut

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