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Transcript
CHAPTER 8 MATRICES AND DETERMINANTS 8.1 Matrix Solutions to Linear Systems • Objectives – Write the augmented matrix for a linear system – Perform matrix row operations – Use matrices & Gaussian elimination to solve systems – Use matrices & Gauss-Jordan elimination to solve systems Solving a system of 3 equations with 3 variables • Graphically, you are attempting to find where 3 planes intersect. • If you find 3 numeric values for (x,y,z), this indicates the 3 planes intersect at that point. Representing a system of equations in a matrix • If a linear system of 3 equations involved 3 variables, each column represents the different variables & constant, and each row represents a separate equation. • Example: Write the following system as a matrix 2x + 3y – 3z = 7 5x + y – 4z = 2 4x + 2y - z = 6 2 3 3 7 5 1 4 2 4 2 1 6 Solving linear systems using Gaussian elimination • Use techniques learned previously to solve equations (addition & substitution) to solve the system • Variables are eliminated, but each column represents a different variable • Perform addition &/or multiplication to simplify rows. Have one row contain 2 zeros, a one, and a constant. This allows you to solve for one variable. • Work up the matrix and solve for the remaining variables. A matrix should look like this after Gaussian elimination is applied 1 0 0 y1 1 0 z1 z2 1 k1 k2 k3 Examples 3 & 4 (p. 541-543) • These examples outline a stepwise approach to use Gaussian elimination. • One row (often the bottom row) will contain (0 0 0 1 constant) using this method. • After the last variable is solved in the bottom equation, substitute in for that variable in the remaining equations. • GO THROUGH EXAMPLES CAREFULLY Question: Must the last row contain (0 0 0 1 constant)? • Yes, in Gaussian elimination, but there are other options. • Look again at example 3, page 539. • If you multiply the first row by (-1) and add it to the 2nd row, the result is (-2 0 0 -12) • What does this mean? -2x = -12, x=6 • By making an informed decision as to what variables to eliminate, we solved for a variable much more quickly! • Next, multiply row 1 by (-1) & add to 3rd row: (-2 2 0 6). Recall x=-6, therefore this becomes -2(6)+2y=6, y=3 Now knowing x & y, solve for z in any row (row 2?) 6 + 3 + 2z = 19, z=5 Solution: (6,3,5) If this method is quicker, why would we use Gaussian elimination? • Using a matrix to solve a system by Gaussian elimination provides a standard, programmable approach. • When computer programs (may be contained in calculators) solve systems. This is the method utilized! 8.2 Inconsistent & Dependent Systems & Their Applications • Objectives – Apply Gaussian elimination to systems without unique solutions – Apply Gaussian elimination to systems with more variables than equations – Solve problems involving systems without unique solutions. How would you know, with Gaussian elimination, that there are no solutions to your system? • When reducing your matrix (attempting to have rows contain only 0’s, 1’s & the constant) a row becomes 0 0 0 0 k • What does that mean? Can you have 0 times anything equal to a non-zero constant? NO! No solution! • Inconsistent system – no solution Graphically, what is happening with an inconsistent system? • Recall, with 3 variables, the equation represents a plane, therefore we are considering the intersection of 3 planes. • If a system is inconsistent, 2 or more of the planes may be parallel OR 2 planes could intersect forming 1 line and a different pair of planes intersect at a different line, therefore there is nothing in common to all three planes. Could there be more than one solution? • Yes! If the planes intersect to form a line, rather than a point, there would be infinitely many solutions. All pts. lying on the line would be solutions. • You can’t state infinitely many points, so you state the general form of all points on the line, in terms of one of the variables. What if your system has 3 variables but only 2 equations? • Graphically, this is the intersection of 2 planes. • 2 planes cannot intersect in 1 point, rather they intersect in 1 line. (or are parallel, thus no solution) • The solution is all points on that line. • The ordered triple is represented as one of the variables (usually z) and the other 2 as functions of that variable: ex: (z+2,3z,z) Dependent system • Notice when there were infinitely many solutions, two variables were stated in terms of the 3rd. In other words, the x & y values are dependent on the value selected for z. • If there are infinitely many solutions, the system is considered to be dependent. 8.3 Matrix Operations & Their Applications • Objectives – Use matrix notation – Understand what is meant by equal matrices – Perform scalar multiplication – Solve matrix equations – Multiply matrices – Describe applied situations with matrix operations What is a matrix? • A set of numbers in rows & columns • m x n describes the dimensions of the matrix (m rows & n columns) • The matrix is contained within brackets. • Example of a 3 x 3 matrix: 4 2 5 1 4 3 0 3 8 Add & Subtract matrices • Only if they are of the same dimensions • Add (or subtract) position by position (i.e. the term in the 3rd row 2nd column of the 1st matrix + the term in the 3rd row 2nd column of the 2nd matrix) Scalar Multiplication • When the multiplier is on the outside of the matrix, every term in the matrix is multiplied by that constant. 1 4 4 16 4 5 2 20 8 • You can combine multiplication and addition of matrices (PRS on next slide) Find 3A + B if 3 1) 6 9 2) 18 3 3) 6 5 4) 10 2 4 6 12 3 9 0 8 1 1 2 3 A ,B 2 3 4 1 Multiplication of matrices • When multiplying matrices, order matters! • The first row of the 1st matrix is multiplied (term by term) by the 1st column of the 2nd matrix. The sum of these products is the new term for the element in the 1st row, 1st column of the new product matrix. • The # columns in 1st matrix MUST equal # rows in 2nd matrix (otherwise terms won’t match up in the term by term multiplication) Multiply: • • • • • • • • • 3 4 3 1 1 2 2 5 4 2 1 0 1)1st row of 1st by 1st column of 2nd (3(3)+4(4)=25) 2) 1st row of 1st by 2nd column of 2nd (3(1)+4(-2)=-5) 3)1st row of 1st by 3rd column of 2nd (3(-1)+4(1)=1) 4)1st row of 1st by 4th column of 2nd (3(2)+4(0)=6) 5)2nd row of 1st by 1st column of 2nd (-2(3)+5(4)=14) 6)2nd row of 1st by 2nd column of 2nd (-2(1)+5(-2)=-12) 7)2nd row of 1st by 3rd column of 2nd (-2(-1)+5(1)=7) 8)2nd row of 1st by 4th column of 2nd (-2(2)+5(0)=-4) (continue on next slide) New matrix is created • Multiplying 1st row by 1st column fills position 11, multiplying 1st row by 2nd column fills position 12, etc • Result: 25 5 1 6 14 12 7 4 • Compare this matrix with the results from the previous slide 8.4 Multiplicative Inverses of Matrices & Matrix Equations • Objectives – Find the multiplicative inverse of a square matrix – Use inverses to solve matrix equations – Encode & decode messages What is the multiplicative inverse of a matrix? • It’s the matrix that you must multiply another matrix by to result in the identity matrix. • What is the identity matrix? It’s the matrix that you would multiply another matrix by that would not change the value of the original matrix. • The identity matrix of a 3x3 matrix is: 1 0 0 0 1 0 0 0 1 How do we find the multiplicative inverse of a matrix? • Example 2, p. 574, outlines the steps. In general, if it’s a 2x2 matrix, you’re finding the value of 4 unknowns using 2systems of equations, each with 2 variables. • Example on next slide for finding a multiplicative inverse of a matrix ( A1 ), which means the multiplicative inverse, NOT 1/A. Find the multiplicative inverse of 5 1 2 2 5 1 a b 1 0 2 2 c d 0 1 5a c 1 8a 2, a 1 / 4, c 1 / 4 2a 2c 0 8 b 1 , b 1 / 8 , d 9 / 40 5b d 0 2b 2d 1 • Multiplicative inverse is: 1 / 4 1 / 8 1 / 4 9 / 40 Quick method for finding the multiplicative inverse of a 2x2 matrix a b 1 d b 1 ,A • If A c d c a ad bc What if the matrix is greater than a 2x2? • Form an augmented matrix A I where A is the original matrix & I is the identity matrix. • Perform elimination and substitution until the original matrix (A) appears as the identity matrix. • The resulting matrix left where the identity matrix began is the multiplicative inverse matrix. ( A1 ) 8.5 Determinants & Cramer’s Rule • Objectives – Evaluate a 2nd-order determinant – Solve a system of linear equations in 2 variables using Cramer’s rule – Evaluate a 3rd-order determinant – Solve a system of linear equations in 3 variables using Cramer’s rule – Use determinants to identify inconsistent & dependent systems – Evaluate higher-order determinants Determinant of a 2x2 matrix • If A is a matrix, the determinant is A 3 2 3 2 A ,A 3(5) (2)4 23 4 5 4 5 When are determinants useful? • They can be used to solve a system of equations • Cramer’s Rule a1 x b1 y c1 a2 x b2 y c2 c1 b1 c2 b2 x ,y a1 b1 a2 b2 a1 a2 a1 a2 c1 c2 b1 b2 Finding a determinant of a 3x3 matrix • More complicated, but it can be done! a1 a2 a3 b1 b2 b3 c1 b2 c2 a1 b3 c3 c2 b1 a2 c3 b3 c1 b1 a3 c3 b2 c1 c2 • It’s often easier to pick your “home row/column” (the one with the multipliers) to be a row/column that has one or more zeros in it. Determinants can be used to solve a linear system in 3 variables CRAMER’S RULE Dy Dx Dz x ,y ,z D D D What is D and Dx , D y , Dz • D is the determinant that results from the coefficients of all variables. • Dx is the determinant that results when each x coefficient is replaced with the given constants. • D y is the determinant that results when each y coefficient is replaced with the given constants. • Dz is the determinant that results when the z coefficients are replaced with the given constants. Find z, given 2x + y = 7 -x + 3y + z = 5 3x + 2y – 4z = 10 2 1 7 1) 2 1 3 2 1 3 ( 2) 2 1 3 1 0 3 1 5 10 1 0 3 1 2 4 1 0 3 1 2 4 1 7 3 5 2 10 2 1 3 3) 2 1 3 2 1 3 ( 4) 2 1 3 1 7 3 5 2 10 1 0 3 1 2 4 1 7 3 5 2 10 1 7 3 1 2 4