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§1.4 Matrix Equation Ax = B: Linear Combination

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§1.4 Matrix Equation Ax = B: Linear Combination x1.4 Matrix Equation A x = b: Linear Combination (I) Matrix-vector Product () Linear Combination (II) Example: 2 4 3 1 2 −1 A = ; x = 3 0 −5 3 4 5 7 Linear Equations in terms of Matrix-vector Product Example: Linear Equations in terms of Matrix-vector Product Example: Linear Equations in terms of Linear Combinations Linear Equations in terms of Linear Combinations 2 3 1 3 4 b1 4 0 14 10 b2 + 4 b1 5 0 7 5 b3 + 3 b1 2 3 1 3 4 b1 (`3)−(1=2)×(`2)!(`3) =) 4 0 14 10 b2 + 4 b1 5 0 0 0 b3 + 3 b1 − 1=2(b2 + 4 b1) Answer: equation Ax = b consistent () b3 − 1=2 b2 + b1 = 0: Existence of Solutions 2 3 2 3 1 3 4 b1 Example: Let A = 4 −4 2 −6 5 ; and b = 4 b2 5 : −3 −2 −7 b3 Question: For what values of b1; b2; b3 is equation Ax = b consistent? 2 3(`2) + (4) × (`1) ! (`2) 1 3 4 b1 (`3) + (3) × (`1) ! (`3) 4 −4 2 −6 b2 5 =) −3 −2 −7 b3 2 3 1 3 4 b1 4 0 14 10 b2 + 4 b1 5 0 0 0 b3 + 3 b1 − 1=2(b2 + 4 b1) Answer: equation Ax = b consistent () b3 − 1=2 b2 + b1 = 0: Existence of Solutions 2 3 2 3 1 3 4 b1 Example: Let A = 4 −4 2 −6 5 ; and b = 4 b2 5 : −3 −2 −7 b3 Question: For what values of b1; b2; b3 is equation Ax = b consistent? 2 3(`2) + (4) × (`1) ! (`2) 2 3 1 3 4 b1 1 3 4 b1 (`3) + (3) × (`1) ! (`3) 4 −4 2 −6 b2 5 =) 4 0 14 10 b2 + 4 b1 5 −3 −2 −7 b3 0 7 5 b3 + 3 b1 (` )−(1=2)×(` )!(` ) 3 =) 2 3 Answer: equation Ax = b consistent () b3 − 1=2 b2 + b1 = 0: Existence of Solutions 2 3 2 3 1 3 4 b1 Example: Let A = 4 −4 2 −6 5 ; and b = 4 b2 5 : −3 −2 −7 b3 Question: For what values of b1; b2; b3 is equation Ax = b consistent? 2 3(`2) + (4) × (`1) ! (`2) 2 3 1 3 4 b1 1 3 4 b1 (`3) + (3) × (`1) ! (`3) 4 −4 2 −6 b2 5 =) 4 0 14 10 b2 + 4 b1 5 −3 −2 −7 b3 0 7 5 b3 + 3 b1 2 3 1 3 4 b1 (`3)−(1=2)×(`2)!(`3) =) 4 0 14 10 b2 + 4 b1 5 0 0 0 b3 + 3 b1 − 1=2(b2 + 4 b1) Existence of Solutions 2 3 2 3 1 3 4 b1 Example: Let A = 4 −4 2 −6 5 ; and b = 4 b2 5 : −3 −2 −7 b3 Question: For what values of b1; b2; b3 is equation Ax = b consistent? 2 3(`2) + (4) × (`1) ! (`2) 2 3 1 3 4 b1 1 3 4 b1 (`3) + (3) × (`1) ! (`3) 4 −4 2 −6 b2 5 =) 4 0 14 10 b2 + 4 b1 5 −3 −2 −7 b3 0 7 5 b3 + 3 b1 2 3 1 3 4 b1 (`3)−(1=2)×(`2)!(`3) =) 4 0 14 10 b2 + 4 b1 5 0 0 0 b3 + 3 b1 − 1=2(b2 + 4 b1) Answer: equation Ax = b consistent () b3 − 1=2 b2 + b1 = 0: (a) ()def (b) ()def (c): Will show (a) () (d) Equivalent Statements on Existence of Solution (I) Will show (a) () (d) Equivalent Statements on Existence of Solution (I) (a) ()def (b) ()def (c): Equivalent Statements on Existence of Solution (I) (a) ()def (b) ()def (c): Will show (a) () (d) U has a pivot in each row. =) Ux = d has solution =) Ax = b has solution. YES! Equivalent Statements (II): (d) () (a) ? I A has pivot in each row =) Ax = b has solution for each b: row echelon (A j b) =) (U j d) ; =) Ax = b has solution. YES! Equivalent Statements (II): (d) () (a) ? I A has pivot in each row =) Ax = b has solution for each b: row echelon (A j b) =) (U j d) ; U has a pivot in each row. =) Ux = d has solution Equivalent Statements (II): (d) () (a) ? I A has pivot in each row =) Ax = b has solution for each b: row echelon (A j b) =) (U j d) ; U has a pivot in each row. =) Ux = d has solution =) Ax = b has solution. YES! Equivalent Statements (II): (d) () (a) ? I A has pivot in each row =) Ax = b has solution for each b: row echelon (A j b) =) (U j d) ; U has a pivot in each row. =) Ux = d has solution =) Ax = b has solution. YES! Ax = b has solution for each b. =) Let d be vector with all components 1. (work row echelon backwards, can find corresponding b) =) Ux = d having solution implies no zero row in U =) A has a pivot in each row. YES! Equivalent Statements (III): (d) () (a) ? I Ax = b has solution for each b =) A has pivot in each row: row echelon (A j b) =) (U j d) ; =) Let d be vector with all components 1. (work row echelon backwards, can find corresponding b) =) Ux = d having solution implies no zero row in U =) A has a pivot in each row. YES! Equivalent Statements (III): (d) () (a) ? I Ax = b has solution for each b =) A has pivot in each row: row echelon (A j b) =) (U j d) ; Ax = b has solution for each b. =) Ux = d having solution implies no zero row in U =) A has a pivot in each row. YES! Equivalent Statements (III): (d) () (a) ? I Ax = b has solution for each b =) A has pivot in each row: row echelon (A j b) =) (U j d) ; Ax = b has solution for each b. =) Let d be vector with all components 1. (work row echelon backwards, can find corresponding b) =) A has a pivot in each row. YES! Equivalent Statements (III): (d) () (a) ? I Ax = b has solution for each b =) A has pivot in each row: row echelon (A j b) =) (U j d) ; Ax = b has solution for each b. =) Let d be vector with all components 1. (work row echelon backwards, can find corresponding b) =) Ux = d having solution implies no zero row in U Equivalent Statements (III): (d) () (a) ? I Ax = b has solution for each b =) A has pivot in each row: row echelon (A j b) =) (U j d) ; Ax = b has solution for each b. =) Let d be vector with all components 1. (work row echelon backwards, can find corresponding b) =) Ux = d having solution implies no zero row in U =) A has a pivot in each row. YES! Example: 3 x1 + 5 x2 − 4 x3 = 0; −3 x1 − 2 x2 + 4 x3 = 0; 6 x1 + x2 − 8 x3 = 0: Augmented matrix (A j b) to row echelon form 0 3 5 −4 0 1 0 3 5 −4 0 1 0 3 5 −4 0 1 @ −3 −2 4 0 A ∼ @ 0 3 0 0 A ∼ @ 0 3 0 0 A 6 1 −8 0 0 −9 0 0 0 0 0 0 x3 is free variable. x1.5 Solution Sets of Linear Systems: Homogeneous Systems Ax = 0 trivial solution: x = 0; any non-zero solution x is non-trivial. Example: 3 x1 + 5 x2 − 4 x3 = 0; −3 x1 − 2 x2 + 4 x3 = 0; 6 x1 + x2 − 8 x3 = 0: Augmented matrix (A j b) to row echelon form 0 3 5 −4 0 1 0 3 5 −4 0 1 0 3 5 −4 0 1 @ −3 −2 4 0 A ∼ @ 0 3 0 0 A ∼ @ 0 3 0 0 A 6 1 −8 0 0 −9 0 0 0 0 0 0 x3 is free variable. x1.5 Solution Sets of Linear Systems: Homogeneous Systems Ax = 0 trivial solution: x = 0; any non-zero solution x is non-trivial. Augmented matrix (A j b) to row echelon form 0 3 5 −4 0 1 0 3 5 −4 0 1 0 3 5 −4 0 1 @ −3 −2 4 0 A ∼ @ 0 3 0 0 A ∼ @ 0 3 0 0 A 6 1 −8 0 0 −9 0 0 0 0 0 0 x3 is free variable. x1.5 Solution Sets of Linear Systems: Homogeneous Systems Ax = 0 trivial solution: x = 0; any non-zero solution x is non-trivial. Example: 3 x1 + 5 x2 − 4 x3 = 0; −3 x1 − 2 x2 + 4 x3 = 0; 6 x1 + x2 − 8 x3 = 0: x3 is free variable. x1.5 Solution Sets of Linear Systems: Homogeneous Systems Ax = 0 trivial solution: x = 0; any non-zero solution x is non-trivial. Example: 3 x1 + 5 x2 − 4 x3 = 0; −3 x1 − 2 x2 + 4 x3 = 0; 6 x1 + x2 − 8 x3 = 0: Augmented matrix (A j b) to row echelon form 0 3 5 −4 0 1 0 3 5 −4 0 1 0 3 5 −4 0 1 @ −3 −2 4 0 A ∼ @ 0 3 0 0 A ∼ @ 0 3 0 0 A 6 1 −8 0 0 −9 0 0 0 0 0 0 x1.5 Solution Sets of Linear Systems: Homogeneous Systems Ax = 0 trivial solution: x = 0; any non-zero solution x is non-trivial. Example: 3 x1 + 5 x2 − 4 x3 = 0; −3 x1 − 2 x2 + 4 x3 = 0; 6 x1 + x2 − 8 x3 = 0: Augmented matrix (A j b) to row echelon form 0 3 5 −4 0 1 0 3 5 −4 0 1 0 3 5 −4 0 1 @ −3 −2 4 0 A ∼ @ 0 3 0 0 A ∼ @ 0 3 0 0 A 6 1 −8 0 0 −9 0 0 0 0 0 0 x3 is free variable.
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