1 / 91

Exploring Linear Transformations: Theory and Applications

Dive into Section 6.1 of Elementary Linear Algebra to learn about linear transformations, images, preimages, operators, and more. Practice with examples and theorems to grasp key concepts and enhance your understanding of this fundamental topic.

bchurch
Download Presentation

Exploring Linear Transformations: Theory and Applications

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. CHAPTER 6LINEAR TRANSFORMATIONS 6.1 Introduction to Linear Transformations 6.2 The Kernel and Range of a Linear Transformation 6.3 Matrices for Linear Transformations 6.4 Transition Matrices and Similarity 6.5 Applications of Linear Transformations Elementary Linear Algebra 投影片設計編製者 R. Larson (7 Edition) 淡江大學 電機系 翁慶昌 教授

  2. CH 6 Linear Algebra Applied Multivariate Statistics (p.298) Circuit Design (p.316) Control Systems (p.308) Weather (p.325) Computer Graphics (p.332)

  3. 6.1 Introduction to Linear Transformations • Function T that maps a vector space V into a vector space W: V: the domain of T W: the codomain of T Elementary Linear Algebra: Section 6.1, p.292

  4. Image of v under T: If v is in V and w is in W such that Then w is called the image of v under T . • the range of T: The set of all images of vectors in V. • the preimage of w: The set of all v in V such that T(v)=w. Elementary Linear Algebra: Section 6.1, p.292

  5. Ex 1: (A function from R2 intoR2 ) (a) Find the image of v=(-1,2). (b) Find the preimage of w=(-1,11) Sol: Thus {(3, 4)} is the preimage of w=(-1, 11). Elementary Linear Algebra: Section 6.1, p.292

  6. Linear Transformation (L.T.): Elementary Linear Algebra: Section 6.1, p.293

  7. Addition in V Addition in W Scalar multiplication in V Scalar multiplication in W • Notes: (1) A linear transformation is said to be operation preserving. (2) A linear transformation from a vector space into itself is called a linear operator. Elementary Linear Algebra: Section 6.1, p.293

  8. Ex 2: (Verifying a linear transformation T from R2 into R2) Pf: Elementary Linear Algebra: Section 6.1, p.293

  9. Therefore, T is a linear transformation. Elementary Linear Algebra: Section 6.1, p.293

  10. Ex 3: (Functions that are not linear transformations) Elementary Linear Algebra: Section 6.1, p.294

  11. Notes: Two uses of the term “linear”. (1) is called a linear function because its graph is a line. (2) is not a linear transformation from a vector space R into R because it preserves neither vector addition nor scalar multiplication. Elementary Linear Algebra: Section 6.1, p.294

  12. Zero transformation: • Identity transformation: • Thm 6.1: (Properties of linear transformations) Elementary Linear Algebra: Section 6.1, p.294

  13. Ex 4: (Linear transformations and bases) Let be a linear transformation such that Find T(2, 3, -2). Sol: (T is a L.T.) Elementary Linear Algebra: Section 6.1, p.295

  14. Ex 5: (A linear transformation defined by a matrix) The function is defined as Sol: (vector addition) (scalar multiplication) Elementary Linear Algebra: Section 6.1, p.295

  15. Thm 6.2: (The linear transformation given by a matrix) Let A be an mn matrix. The function T defined by is a linear transformation from Rn into Rm. • Note: Elementary Linear Algebra: Section 6.1, p.296

  16. Ex 7: (Rotation in the plane) Show that the L.T. given by the matrix has the property that it rotates every vector in R2 counterclockwise about the origin through the angle . Sol: (polar coordinates) r： the length of v ：the angle from the positive x-axis counterclockwise to the vector v Elementary Linear Algebra: Section 6.1, p.297

  17. r：the length of T(v)  +：the angle from the positive x-axis counterclockwise to the vector T(v) Thus, T(v) is the vector that results from rotating the vector v counterclockwise through the angle . Elementary Linear Algebra: Section 6.1, p.297

  18. Ex 8: (A projection in R3) The linear transformation is given by is called a projection in R3. Elementary Linear Algebra: Section 6.1, p.298

  19. Ex 9: (A linear transformation from Mmn into Mnm ) Show that T is a linear transformation. Sol: Therefore, T is a linear transformation from Mmn into Mnm. Elementary Linear Algebra: Section 6.1, p.298

  20. Key Learning in Section 6.1 • Find the image and preimage of a function. • Show that a function is a linear transformation, and find a linear transformation.

  21. Keywords in Section 6.1 • function: 函數 • domain: 論域 • codomain: 對應論域 • image of v under T: 在T映射下v的像 • range of T: T的值域 • preimage of w: w的反像 • linear transformation: 線性轉換 • linear operator: 線性運算子 • zero transformation: 零轉換 • identity transformation: 相等轉換

  22. Ex 1: (Finding the kernel of a linear transformation) Sol: 6.2 The Kernel and Range of a Linear Transformation • Kernel of a linear transformation T: Let be a linear transformation Then the set of all vectors v in V that satisfy is called the kernel of T and is denoted by ker(T). Elementary Linear Algebra: Section 6.2, p.303

  23. Ex 3: (Finding the kernel of a linear transformation) Sol: • Ex 2: (The kernel of the zero and identity transformations) (a) T(v)=0 (the zero transformation ) (b) T(v)=v (the identity transformation ) Elementary Linear Algebra: Section 6.2, p.303

  24. Ex 5: (Finding the kernel of a linear transformation) Sol: Elementary Linear Algebra: Section 6.2, p.304

  25. Elementary Linear Algebra: Section 6.2, p.304

  26. Thm 6.3: (The kernel is a subspace of V) The kernel of a linear transformation is a subspace of the domain V. Pf: • Note: The kernel of T is sometimes called the nullspace of T. Elementary Linear Algebra: Section 6.2, p.305

  27. Ex 6: (Finding a basis for the kernel) Find a basis for ker(T) as a subspace of R5. Elementary Linear Algebra: Section 6.2, p.30 5

  28. Sol: Elementary Linear Algebra: Section 6.2, p.305

  29. Corollary to Thm 6.3: • Range of a linear transformation T: Elementary Linear Algebra: Section 6.2, p.305

  30. Thm 6.4: (The range of T is a subspace of W) Pf: Elementary Linear Algebra: Section 6.2, p.306

  31. Corollary to Thm 6.4: • Notes: Elementary Linear Algebra: Section 6.2, p.306

  32. Ex 7: (Finding a basis for the range of a linear transformation) Find a basis for the range of T. Elementary Linear Algebra: Section 6.2, p.307

  33. Sol: Elementary Linear Algebra: Section 6.2, p.307

  34. Nullity of a linear transformation T:V→W: • Note: • Rank of a linear transformation T:V→W: Elementary Linear Algebra: Section 6.2, p.307

  35. Thm 6.5: (Sum of rank and nullity) Pf: Elementary Linear Algebra: Section 6.2, p.307

  36. Ex 8: (Finding the rank and nullity of a linear transformation) Sol: Elementary Linear Algebra: Section 6.2, p.308

  37. Ex 9: (Finding the rank and nullity of a linear transformation) Sol: Elementary Linear Algebra: Section 6.2, p.308

  38. one-to-one not one-to-one • One-to-one: Elementary Linear Algebra: Section 6.2, p.309

  39. Onto: (T is onto W when W is equal to the range of T.) Elementary Linear Algebra: Section 6.2, p.309

  40. Thm 6.6: (One-to-one linear transformation) Pf: Elementary Linear Algebra: Section 6.2, p.309

  41. Ex 10: (One-to-one and not one-to-one linear transformation) Elementary Linear Algebra: Section 6.2, p.309

  42. Thm 6.8: (One-to-one and onto linear transformation) Pf: • Thm 6.7: (Onto linear transformation) Elementary Linear Algebra: Section 6.2, p.310

  43. Ex 11: Sol: Elementary Linear Algebra: Section 6.2, p.310

  44. Thm 6.9: (Isomorphic spaces and dimension) Two finite-dimensional vector space V and W are isomorphic if and only if they are of the same dimension. Pf: • Isomorphism: Elementary Linear Algebra: Section 6.2, p.311

  45. It can be shown that this L.T. is both 1-1 and onto. Thus V and W are isomorphic. Elementary Linear Algebra: Section 6.2, p.311

  46. Ex 12: (Isomorphic vector spaces) The following vector spaces are isomorphic to each other. Elementary Linear Algebra: Section 6.2, p.311

  47. Key Learning in Section 6.2 • Find the kernel of a linear transformation. • Find a basis for the range, the rank, and the nullity of a linear transformation. • Determine whether a linear transformation is one-to-one or onto. • Determine whether vector spaces are isomorphic.

  48. Keywords in Section 6.2 • kernel of a linear transformation T: 線性轉換T的核空間 • range of a linear transformation T: 線性轉換T的值域 • rank of a linear transformation T: 線性轉換T的秩 • nullity of a linear transformation T: 線性轉換T的核次數 • one-to-one: 一對一 • onto: 映成 • isomorphism(one-to-one and onto): 同構 • isomorphic space: 同構的空間

  49. 6.3 Matrices for Linear Transformations • Two representations of the linear transformation T:R3→R3 : • Three reasons for matrix representation of a linear transformation: • It is simpler to write. • It is simpler to read. • It is more easily adapted for computer use. Elementary Linear Algebra: Section 6.3, p.314

  50. Thm 6.10: (Standard matrix for a linear transformation) Elementary Linear Algebra: Section 6.3, p.314

More Related