# 5.3 Orthogonal Transformations This picture is from knot theory

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5.3 Orthogonal Transformations This picture is from knot theory Slide 2 Recall Slide 3 The transpose of a matrix The transpose of a matrix is made by simply taking the columns and making them rows (and vice versa) Example: Slide 4 Properties of orthogonal matrices (Q) An orthogonal matrix (probably better name would be orthonormal). Is a matrix such that each column vector is orthogonal to ever other column vector in the matrix. Each column in the matrix has length 1. We created these matrices using the Gram Schmidt process. We would now like to explore their properties. Slide 5 Properties of Q Note: Q is a notation to denote that some matrix A is orthogonal Q T Q = I (note: this is not normally true for QQ T ) If Q is square, then Q T = Q -1 The Columns of Q form an orthonormal basis of R n The transformation Qx=b preserves length (for every x entered in the equation the resulting b vector is the same length. (proof is in the book on page 211) The transformation Q preserves orthogonality (proof on next slide) Slide 6 Orthogonal transformations preserve orthogonality Why? If distances are preserved then an angle that is a right angle before the transformation must still be right triangle after the transformation due to the Pythagorean theorem. Slide 7 Example 1 Is the rotation an orthogonal transformation? Slide 8 Solution to Example 1 Yes, because the vectors are orthogonal Slide 9 Orthogonal transformations and orthogonal bases 1)A linear transformation R from R n to R n is orthogonal if and only if the vectors form an orthonormal basis of R n 2)An nxn matrix A is orthogonal if and only if its columns form an orthonormal bases of R n Slide 10 Problems 2 and 4 Which of the following matrices are orthogonal? Slide 11 Solutions to 2 and 4 Slide 12 Properties of orthogonal matrices The product AB of two orthogonal nxn matrices is orthogonal The inverse A -1 of an orthogonal nxn matrix A is orthogonal If we multiply an orthogonal matrix times a constant will the result be an orthogonal matrix? Why? Slide 13 Problems 6,8 and 10 If A and B represent orthogonal matrices, which of the following are also orthogonal? 10. B -1 AB 8. A + B 6. -B Slide 14 Solutions to 6, 8 and 10 The product to two orthogonal matrices is orthogonal The inverse of an orthogonal nxn matrix is orthogonal Slide 15 Properties of the transpose Slide 16 Symmetric Matrix A matrix is symmetric of A T = A Symmetric matrices must be square. The symmetric 2x2 matrices have the form: If a A T = -A, then the matrix is called skew symmetric Slide 17 Proof of transpose properties Slide 18 Problems 14,16,18 If A and B are symmetric and B is invertible. Which of the following must be symmetric as well? 14. B16. A + B Slide 19 Solutions to 14,16,18 Slide 20 Problems 22 and 24 A and B are arbitrary nxn matrices. Which of the following must be symmetric? 22. BB T 24. A T BA Slide 21 Solutions to 22 and 24 A T BA Slide 22 Problem 36 Find and orthogonal matrix of the form _ 2/3 1/2 a _ 2/3 -1/2 b 1/3 0 c [ ] Slide 23 Problem 36 Solution Slide 24 Homework: p. 218 1-25 odd, 33-37 all A student was learning to work with Orthogonal Matrices (Q) He asked his another student to help him learn to do operations with them: Student 1: What is 7Q + 3Q? Student 2: 10Q Student 1: Youre Welcome (Question: Is 10Q an orthogonal matrix?) Slide 25 Proof Q preserves orthogonality See next slide for a picture Slide 26 Orthogonal Transformations and Orthogonal matrices A linear transformation T from R n to R n is called orthogonal if it preserves the lengths of vectors. ||T(x)|| = ||x|| If T(x) is an orthogonal transformation then we say that A is an orthonormal matrix.

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