Discrete-Chapter 03 Matrices

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Discrete-Chapter 03 Matrices

  1. 1. Matrices - 03 CSC1001 Discrete Mathematics 1 CHAPTER เมตริกซ์ 3 (Matrices) 1 Introduction to Matrices1. Definition of Matrices Matrices are used throughout discrete mathematics to express relationships between elements in sets.Matrices will be used in models of communications networks and transportation systems. Many algorithms willbe developed that use these matrix models. Definition 1 A matrix is a rectangular array of numbers. A matrix with m rows and n columns is called an m × n matrix. The plural of matrix is matrices. A matrix with the same number of rows as columns is called square. We use boldface uppercase letters to represent matrices. Definition 2 Two matrices are equal if they have the same number of rows and the same number of columns and the corresponding entries in every position are equal.Example 1 (4 points) Define a size of m × n matrix. ⎡1 2 3⎤ ⎢1 3⎥ ⎢ 2 ⎥ ⎡− 3 5 7 ⎤1) …………………………………………… 2) ⎢ 9 − 7 − 6⎥ …………………….……………… ⎢4 5 6⎥ ⎣ ⎦ ⎢ ⎥ ⎣4 5 6⎦ ⎡0 0⎤ ⎢0 ⎡1 1 1 1 1⎤ ⎢ 0⎥ ⎥ ⎢1 1 1 1 1⎥3) ……………………………………………….. 4) ⎢ ⎥ ……………………………………... ⎢0 0⎥ ⎢ ⎥ ⎢1 1 1 1 1⎥ ⎣ ⎦ ⎣0 0⎦Example 2 (4 points) Is matrix equal or not? why? ⎡1 2 3⎤ ⎡1 2 3 0⎤1) A = ⎢4 B= ………………………………………………………………………………….. ⎣ 5 6⎥ ⎦ ⎢4 ⎣ 5 6 0⎥⎦ ⎡1 2 3⎤ ⎡1 5 3⎤2) A = ⎢4 B= ……………………………………………………………………………………… ⎣ 5 6⎥ ⎦ ⎢4 ⎣ 2 6⎥ ⎦ ⎡1 2 3⎤ ⎡1 2 3⎤3) A = ⎢4 B= ……………………………………………………………………………………… ⎣ 5 6⎥ ⎦ ⎢4 ⎣ 5 6⎥ ⎦ ⎡0 0 1⎤ ⎡0 0 0⎤4) A = ⎢0 B= ……………………………………………………………………………………… ⎣ 0 0⎥ ⎦ ⎢1 ⎣ 0 0⎥ ⎦มหาวิทยาลัยราชภัฏสวนส ุนันทา (ภาคการศึกษาที่ 2/2555) เรียบเรียงโดย อ.วงศ์ยศ เกิดศรี
  2. 2. 2 CSC1001 Discrete Mathematics 03 - Matrices Definition 3 Let m and n be positive integers and let ⎡ a11 a12 L a 1n ⎤ ⎢a a 22 L a 2n ⎥ A= ⎢ 21 ⎥ ⎢ M M M M ⎥ ⎢ ⎥ ⎣a m1 am2 L a mn ⎦ ⎡ a1 j ⎤ ⎢a ⎥ The ith row of A is the 1 × n matrix [ai1 ai 2 L ain ] . The j th column of A is the m × 1 matrix ⎢ 2j⎥ ⎢ M ⎥ ⎢ ⎥ ⎢ a mj ⎥ ⎣ ⎦ The (i, j )th element or entry of A is the element aij , that is, the number in the ith row and j th column of A. A convenient shorthand notation for expressing the matrix A is to write A = [aij], which indicates that A is the matrix with its (i, j )th element equal to aij.Example 3 (8 points) Let A is 5 × 4 matrix ⎡1 3 5 7⎤ ⎢2 4 6 8⎥ ⎢ ⎥A= ⎢0 1 0 1⎥ ⎢ ⎥ ⎢1 2 3 4⎥ ⎢5 ⎣ 6 7 8⎥ ⎦1) Write W is 1 × 4 matrix at the 3rd row of A 2) Write X is 1 × 4 matrix at the 5th row of A3) Write Y is 5 × 1 matrix at the 4th column of A 4) Write Z is 5 × 1 matrix at the 1st column of A2. Matrix Arithmetic Definition 4 Let A = [aij] and B = [bij] be m × n matrices. The sum of A and B, denoted by A + B, is the m × n matrix that has aij + bij as its (i, j )th element. In other words, A + B = [aij + bij].มหาวิทยาลัยราชภัฏสวนส ุนันทา (ภาคการศึกษาที่ 2/2555) เรียบเรียงโดย อ.วงศ์ยศ เกิดศรี
  3. 3. Matrices - 03 CSC1001 Discrete Mathematics 3Example 4 (10 points) Let A and B be m × n matrices. Find A + B ⎡1 2 3⎤A= ⎢4 ⎣ 5 6⎥ ⎦ ⎡1 5 3⎤B= ⎢4 ⎣ 2 6⎥ ⎦Example 5 (10 points) Let A and B be m × n matrices. Find 3A + B ⎡− 1 − 2 − 3 − 4⎤A= ⎢1 2 3 4⎥ ⎢ ⎥ ⎢0 ⎣ 2 4 6⎥⎦ ⎡2 5 −7 1 ⎤B= ⎢− 1 9 4 − 1⎥ ⎢ ⎥ ⎢ 1 − 11 ⎣ 7 0⎥ ⎦Example 6 (10 points) Let A and B be m × n matrices. Find A - 2B ⎡− 1 2 − 3 4 ⎤ ⎢0 8 3 4⎥A= ⎢ ⎥ ⎢ 2 −6 5 7⎥ ⎢ ⎥ ⎣− 1 − 6 5 − 3⎦ ⎡0 5 6 1⎤ ⎢ 2 1 1 9⎥B= ⎢ ⎥ ⎢ 3 −1 − 4 2 ⎥ ⎢ ⎥ ⎣− 2 − 7 0 − 1⎦Example 7 (10 points) Let A be m × n matrix. Prove that A + A + A = 3A ⎡1 2 3⎤A= ⎢0 3 1 ⎥ ⎢ ⎥ ⎢ 2 3 2⎥ ⎣ ⎦ Definition 5 Let A be an m × k matrix and B be a k × n matrix. The product of A and B, denoted by AB, is the m × n matrix with its (i, j )th entry equal to the sum of the products of the corresponding elements from the ith row of A and the jth column of B. In other words, if AB = [cij ], then cij = ai1b1j + ai2b2j + … +aikbkj .มหาวิทยาลัยราชภัฏสวนส ุนันทา (ภาคการศึกษาที่ 2/2555) เรียบเรียงโดย อ.วงศ์ยศ เกิดศรี
  4. 4. 4 CSC1001 Discrete Mathematics 03 - Matrices Figure: The Product of A = [aij ] and B = [bij ]Example 8 (10 points) Let A be m × k matrix and B be k × n matrix. Find AB ⎡2 2 −3 1 ⎤ ⎡2 1 5⎤ ⎢− 1 2A= ⎢ 4 7 2⎥ B= ⎢ 5 2⎥⎥ ⎣ ⎦ ⎢ 3 − 3 4 − 5⎥ ⎣ ⎦Example 9 (10 points) Let A be m × k matrix and B be k × n matrix. Find AB ⎡ 2 −1 4 ⎤ ⎢ − 1 2 − 2⎥ ⎢ ⎥ ⎡2 1⎤A= ⎢ 3 −3 4 ⎥ B= ⎢− 1 3 ⎥ ⎢ ⎥ ⎢ ⎥ ⎢5 2 2⎥ ⎢ 2 − 3⎥ ⎣ ⎦ ⎢ 6 −1 3 ⎥ ⎣ ⎦Example 10 (10 points) Let A be m × k matrix and B be k × n matrix. Find AB ⎡− 1 0 ⎤ ⎡ 2 2 3⎤ ⎢ 1 − 2⎥A= ⎢ 3 4 4⎥ B= ⎢ ⎥ ⎣ ⎦ ⎢3 0⎥ ⎣ ⎦มหาวิทยาลัยราชภัฏสวนส ุนันทา (ภาคการศึกษาที่ 2/2555) เรียบเรียงโดย อ.วงศ์ยศ เกิดศรี
  5. 5. Matrices - 03 CSC1001 Discrete Mathematics 5Example 11 (10 points) Let A and B be n × n matrices. Prove that AB ≠ BA ⎡1 2 3⎤ ⎡ 2 0 0⎤A= ⎢0 3 1 ⎥ B= ⎢1 2 1 ⎥ ⎢ ⎥ ⎢ ⎥ ⎢ 2 3 2⎥ ⎣ ⎦ ⎢ 5 2 4⎥ ⎣ ⎦Example 12 (20 points) Let A, B and C be m × n matrices. Find (A + 2B)(3C) ⎡1 2 1 2⎤ ⎡4 5 1 2⎤ ⎡ 2 − 1⎤ ⎢3 4 0 4⎥ ⎢2 2 2 1⎥ ⎢0 2⎥A= ⎢ ⎥ B= ⎢ ⎥ C= ⎢ ⎥ ⎢2 6 7 3⎥ ⎢1 4 2 1⎥ ⎢− 2 1 ⎥ ⎢ ⎥ ⎢ ⎥ ⎢ ⎥ ⎣1 2 2 1⎦ ⎣8 9 4 2⎦ ⎣ 3 4⎦มหาวิทยาลัยราชภัฏสวนส ุนันทา (ภาคการศึกษาที่ 2/2555) เรียบเรียงโดย อ.วงศ์ยศ เกิดศรี
  6. 6. 6 CSC1001 Discrete Mathematics 03 - Matrices3. Transposes and Powers of Matrices Definition 6 The identity matrix of order n is the n × n matrix In = [δij ], where δij = 1 if i = j and δij = 0 if i ≠ j . Hence ⎡1 0 L 0⎤ ⎢0 ⎡1 0 0 ⎤ ⎢ 1 L 0⎥ ⎥ ⎢0 1 0 ⎥ In = for example I3 = ⎢ ⎥ ⎢M M O M⎥ ⎢ ⎥ ⎢0 0 1 ⎥ ⎣ ⎦ ⎣0 0 L 1⎦ Theorem 1 Multiplying a matrix by an appropriately sized identity matrix does not change this matrix. In other words, when A is an m × n matrix, we have AIn = ImA = A Theorem 2 Powers of square matrices can be defined. When A is an n × n matrix, we have A0 = In , Ar = AAA…A r timesExample 13 (5 points) Show identity matrix I1, I2 and I4Example 14 (10 points) Let A be m × n matrix. Prove that AIn = ImA = A ⎡ 2 2 3⎤A= ⎢ 3 4 4⎥ ⎣ ⎦Example 15 (10 points) Let A be n × n matrix. Find A3 ⎡1 2⎤A= ⎢3 1 ⎥ ⎣ ⎦มหาวิทยาลัยราชภัฏสวนส ุนันทา (ภาคการศึกษาที่ 2/2555) เรียบเรียงโดย อ.วงศ์ยศ เกิดศรี
  7. 7. Matrices - 03 CSC1001 Discrete Mathematics 7 Definition 7 Let A = [aij] be an m × n matrix. The transpose of A, denoted by At, is the n × m matrix obtained by interchanging the rows and columns of A. In other words, if At = [bij], then bij = aji for i = 1, 2, … , n and j = 1, 2, … , m. Definition 8 A square matrix A is called symmetric if A = At . Thus A = [aij] is symmetric if aij = aji for all i and j with 1 ≤ i ≤ n and 1 ≤ j ≤ n. Figure: A Symmetric Matrix or Square MatrixExample 16 (5 points) Let A be m × n matrix. Find At ⎡ 2 2 3⎤A= ⎢ 3 4 4⎥ ⎣ ⎦Example 17 (5 points) Let A be m × n matrix. Find At ⎡ 2 − 1⎤ ⎢0 2⎥A= ⎢ ⎥ ⎢− 2 1 ⎥ ⎢ ⎥ ⎣ 3 4⎦Example 18 (5 points) Let A be m × n matrix. Find At ⎡1 2 3⎤A= ⎢0 3 1 ⎥ ⎢ ⎥ ⎢ 2 3 2⎥ ⎣ ⎦มหาวิทยาลัยราชภัฏสวนส ุนันทา (ภาคการศึกษาที่ 2/2555) เรียบเรียงโดย อ.วงศ์ยศ เกิดศรี
  8. 8. 8 CSC1001 Discrete Mathematics 03 - MatricesExample 19 (5 points) Let A be m × n matrix. Show that A is a square matrix. ⎡1 2 3 1⎤ ⎢2 2 0 5⎥A= ⎢ ⎥ ⎢3 0 3 0⎥ ⎢ ⎥ ⎣1 5 0 2⎦Example 20 (5 points) Let A be m × n matrix. Show that A is not a square matrix. ⎡0 1 0 1⎤ ⎢0 0 0 0⎥A= ⎢ ⎥ ⎢1 1 0 1⎥ ⎢ ⎥ ⎣0 1 1 0⎦Example 21 (5 points) Let A be m × n matrix. Is A a square matrix? why? ⎡1 0 1 1⎤ ⎢0 1 0 1⎥A= ⎢ ⎥ ⎢1 0 0 1⎥ ⎢ ⎥ ⎣1 1 1 1⎦4. Zero–One Matrices A matrix all of whose entries are either 0 or 1 is called a zero–one matrix. This arithmetic is based on theBoolean operations ∧ and ∨ , which operate on pairs of bits, defined by ⎧1, if b1 = b 2 = 1 b1 ∧ b 2 = ⎨ ⎩0, otherwise ⎧1, if b1 = 1 or b 2 = 1 b1 ∨ b 2 = ⎨ ⎩0, otherwise Definition 9 Let A = [aij] and B = [bij] be m × n zero–one matrices. Then the join of A and B is the zero–one matrix with (i, j )th entry aij ∨ bij . The join of A and B is denoted by A ∨ B. The meet of A and B is the zero–one matrix with (i, j )th entry aij ∧ bij . The meet of A and B is denoted by A ∧ B.Example 22 (5 points) Let A and B be m × n zero–one matrices. Find A ∨ B ⎡1 0 1 1⎤ ⎡0 1 0 1⎤ ⎢0 1 0 1⎥ ⎢0 0 0 0⎥A= ⎢ ⎥ B= ⎢ ⎥ ⎢1 0 0 1⎥ ⎢1 1 0 1⎥ ⎢ ⎥ ⎢ ⎥ ⎣1 1 1 1⎦ ⎣0 1 1 0⎦มหาวิทยาลัยราชภัฏสวนส ุนันทา (ภาคการศึกษาที่ 2/2555) เรียบเรียงโดย อ.วงศ์ยศ เกิดศรี
  9. 9. Matrices - 03 CSC1001 Discrete Mathematics 9Example 23 (5 points) Let A and B be m × n zero–one matrices. Find A ∨ B ⎡1 0 0⎤ ⎡1 0 0⎤ ⎢0 1 1⎥ ⎢1 1 1⎥A= ⎢ ⎥ B= ⎢ ⎥ ⎢0 1 1⎥ ⎢1 1 1⎥ ⎢ ⎥ ⎢ ⎥ ⎣0 0 1⎦ ⎣1 0 0⎦Example 24 (5 points) Let A and B be m × n zero–one matrices. Find A ∧ B ⎡1 0 1 1⎤ ⎡1 1 0 1⎤ ⎢1 1 0 0⎥ ⎢0 0 0 0⎥A= ⎢ ⎥ B= ⎢ ⎥ ⎢1 0 0 0⎥ ⎢1 0 1 1⎥ ⎢ ⎥ ⎢ ⎥ ⎣1 0 1 1⎦ ⎣0 0 1 0⎦Example 25 (5 points) Let A and B be m × n zero–one matrices. Find A ∧ B ⎡1 0 0⎤ ⎡1 0 0⎤ ⎢0 1 1⎥ ⎢1 1 1⎥A= ⎢ ⎥ B= ⎢ ⎥ ⎢0 1 1⎥ ⎢1 1 1⎥ ⎢ ⎥ ⎢ ⎥ ⎣0 0 1⎦ ⎣1 0 0⎦Example 26 (10 points) Let A, B and C be m × n zero–one matrices. Find A ∨ (B ∧ C) ⎡1 0 1 1⎤ ⎡1 1 0 1⎤ ⎡0 1 0 1⎤ ⎢1 1 0 0⎥ ⎢0 0 0 0⎥ ⎢0 0 0 0⎥A= ⎢ ⎥ B= ⎢ ⎥ C= ⎢ ⎥ ⎢1 0 0 0⎥ ⎢1 0 1 1⎥ ⎢1 1 0 1⎥ ⎢ ⎥ ⎢ ⎥ ⎢ ⎥ ⎣1 0 1 1⎦ ⎣0 0 1 0⎦ ⎣0 1 1 0⎦ Definition 10 Let A = [aij] be an m × k zero–one matrix and B = [bij] be a k × n zero–one matrix. Then the Boolean product of A and B, denoted by A . B, is the m × n matrix with (i, j)th entry cij where cij = (ai1 ∧ b1j) ∨ (ai2 ∧ b2j) ∨ … ∨ (aik ∧ bkj)มหาวิทยาลัยราชภัฏสวนส ุนันทา (ภาคการศึกษาที่ 2/2555) เรียบเรียงโดย อ.วงศ์ยศ เกิดศรี
  10. 10. 10 CSC1001 Discrete Mathematics 03 - MatricesExample 27 (10 points) Let A be m × k zero–one matrix and B be k × n zero–one matrix. Find A . B ⎡1 0 0 1 ⎤ ⎡1 1 0⎤ ⎢1 1 0 0 ⎥A= ⎢1 0 0⎥ B= ⎢ ⎥ ⎣ ⎦ ⎢0 0 0 1 ⎥ ⎣ ⎦Example 28 (10 points) Let A be m × k zero–one matrix and B be k × n zero–one matrix. Find A . B ⎡0 1 1⎤ ⎡0 1 1 1 1 ⎤A= ⎢0 0 1⎥ B= ⎢1 0 0 0 0 ⎥ ⎢ ⎥ ⎢ ⎥ ⎢1 1 1⎥ ⎣ ⎦ ⎢0 0 0 1 1 ⎥ ⎣ ⎦Example 29 (10 points) Let A be m × k zero–one matrix and B be k × n zero–one matrix. Find A . B ⎡1 0 ⎤ ⎡1 1 1 ⎤ ⎢0 1 ⎥A= ⎢0 0 0 ⎥ B= ⎢ ⎥ ⎣ ⎦ ⎢1 1 ⎥ ⎣ ⎦มหาวิทยาลัยราชภัฏสวนส ุนันทา (ภาคการศึกษาที่ 2/2555) เรียบเรียงโดย อ.วงศ์ยศ เกิดศรี

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