線性代數
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課程簡介
- 資源下載
- Basic Concepts on Matrices and Vectors(1)
- Basic Concepts on Matrices and Vectors(2)
- Basic Concepts on Matrices and Vectors(3)
- Basic Concepts on Matrices and Vectors(4)
- Basic Concepts on Matrices and Vectors(5)
- System of Linear Equations(1)
- System of Linear Equations(2)
- Gaussian Elimination(1)
- Gaussian Elimination(2)
- The language of set theory
- Span of a Set of Vectors(1)
- Span of a Set of Vectors(2)
- Linear Dependence and Linear Independence(1)
- Linear Dependence and Linear Independence(2)
- Matrix Multiplication
- Invertibility and Elementary Matrices
- Column Correspondence Theorem
- The Inverse of a Matrix(1)
- The Inverse of a Matrix(2)
- Linear Transformations and Matrices(1)
- Linear Transformations and Matrices(2)
- Composition and Invertibility of Linear Transformations(1)
- Composition and Invertibility of Linear Transformations(2)
- Determinants(1)
- Determinants(2)
- Subspaces and their properties
- Basis and DimensionⅠ(1)
- Basis and DimensionⅠ(2)
- The Dimension of Subspaces associated with a Matrix
- Coordinate Systems
- Matrix Representations of Linear OperatorsⅠ
- Eigenvalues, Eigenvectors, and Diagonalization
- The Characteristic Polynomial(1)
- The Characteristic Polynomial(2)
- Diagonalization of Matrices(1)
- Diagonalization of Matrices(2)
- The Geometry of Vectors Dot Product(1)
- The Geometry of Vectors Dot Product(2)
- Orthogonal Vectors(1)
- Orthogonal Vectors(2)
- Orthogonal Projections(1)
- Orthogonal Projections(2)
- Least Squares Approximations and Orthogonal Projection Matrices
- Orthogonal Matrices and Operators
- Symmetric Matrices(1)
- Symmetric Matrices(2)
- Symmetric Matrices(3)
- Symmetric Matrices(4)
- Vector Spaces and Their Subspaces(1)
- Vector Spaces and Their Subspaces(2)
- Vector Spaces and Their Subspaces(3)
- Vector Spaces and Their Subspaces(4)
- Linear Transformation(1)
- Linear Transformation(2)
- Linear Transformation(3)
- Basis and DimensionⅡ(1)
- Basis and DimensionⅡ(3)
- Basis and Dimension(3)
- Matrix Representations of Linear OperatorsⅡ(1)
- Matrix Representations of Linear OperatorsⅡ(2)
- The Matrix Representations of the Inverse of an Invertible Linear Operator(1)
- The Matrix Representations of the Inverse of an Invertible Linear Operator(2)
- Eigenvalues and Eigenvectors of a Matrix Representations of a Linear Operator
- Inner Product Spaces(1)
- Inner Product Spaces(2)
- Inner Product Spaces(3)
- Inner Product Spaces(4)
- Inner Product Spaces(5)

本月點閱|19,308 次
授課日期|2014 年 2 月
線性代數
Linear Algebra
蘇柏青
學分數:3 學分
開課單位:電機工程學系
本課程共 68 講| 68
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課程概述
本課程是線性代數的入門課程。線性代數係以「向量空間」(Vector Space)為核心概念之數學工具,擁有極廣泛之應用,非常值得理工商管等科系大學部同學深入修習,作為日後專業應用之基礎。 向量空間乃是代數中較為抽象的概念。為使同學能循序吸收理解線性代數的原理,我們將從大家較熟悉的矩陣、以及多元一次系統方程式開始為大家做入門介紹。