線性代數

  1. 課程簡介
  2. 資源下載
  3. Basic Concepts on Matrices and Vectors (1)
  4. Basic Concepts on Matrices and Vectors (2)
  5. Basic Concepts on Matrices and Vectors (3)
  6. Basic Concepts on Matrices and Vectors (4)
  7. Basic Concepts on Matrices and Vectors (5)
  8. System of Linear Equations (1)
  9. System of Linear Equations (2)
  10. Gaussian Elimination (1)
  11. Gaussian Elimination (2)
  12. The language of set theory
  13. Span of a Set of Vectors (1)
  14. Span of a Set of Vectors (2)
  15. Linear Dependence and Linear Independence (1)
  16. Linear Dependence and Linear Independence (2)
  17. Matrix Multiplication
  18. Invertibility and Elementary Matrices
  19. Column Correspondence Theorem
  20. The Inverse of a Matrix (1)
  21. The Inverse of a Matrix (2)
  22. Linear Transformations and Matrices (1)
  23. Linear Transformations and Matrices (2)
  24. Composition and Invertibility of Linear Transformations (1)
  25. Composition and Invertibility of Linear Transformations (2)
  26. Determinants (1)
  27. Determinants (2)
  28. Subspaces and their properties
  29. Basis and Dimension (1)
  30. Basis and Dimension (2)
  31. The Dimension of Subspaces associated with a Matrix
  32. Coordinate Systems
  33. Matrix Representations of Linear Operators
  34. Eigenvalues, Eigenvectors, and Diagonalization
  35. The Characteristic Polynomial (1)
  36. The Characteristic Polynomial (2)
  37. Diagonalization of Matrices (1)
  38. Diagonalization of Matrices (2)
  39. The Geometry of Vectors Dot Product (1)
  40. The Geometry of Vectors Dot Product (2)
  41. Orthogonal Vectors (1)
  42. Orthogonal Vectors (2)
  43. Orthogonal Projections (1)
  44. Orthogonal Projections (2)
  45. Least Squares Approximations and Orthogonal Projection Matrices
  46. Orthogonal Matrices and Operators
  47. Symmetric Matrices (1)
  48. Symmetric Matrices (2)
  49. Symmetric Matrices (3)
  50. Symmetric Matrices (4)
  51. Vector Spaces and Their Subspaces (1)
  52. Vector Spaces and Their Subspaces (2)
  53. Vector Spaces and Their Subspaces (3)
  54. Vector Spaces and Their Subspaces (4)
  55. Linear Transformation (1)
  56. Linear Transformation (2)
  57. Linear Transformation (3)
  58. Basis and Dimension (1)
  59. Basis and Dimension (2)
  60. Basis and Dimension (3)
  61. Matrix Representations of Linear Operators (1)
  62. Matrix Representations of Linear Operators (2)
  63. The Matrix Representations of the Inverse of an Invertible Linear Operator (1)
  64. The Matrix Representations of the Inverse of an Invertible Linear Operator (2)
  65. Eigenvalues and Eigenvectors of a Matrix Representations of a Linear Operator
  66. Inner Product Spaces (1)
  67. Inner Product Spaces (2)
  68. Inner Product Spaces (3)
  69. Inner Product Spaces (4)
  70. Inner Product Spaces (5)
線性代數

本月點閱｜7,988 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 34 講｜ 影片數量 68 教材數量 33 參考資料數量 0

本作品除另有註明外，採創用 CC「姓名標示-非商業性-相同方式分享」3.0 臺灣版授權釋出。

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。

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