Section 8.4: Determinants

Slides:



Advertisements
Similar presentations
Elementary Linear Algebra Anton & Rorres, 9th Edition
Advertisements

5.4. Additional properties Cofactor, Adjoint matrix, Invertible matrix, Cramers rule. (Cayley, Sylvester….)
Chap. 3 Determinants 3.1 The Determinants of a Matrix
Section 3.1 The Determinant of a Matrix. Determinants are computed only on square matrices. Notation: det(A) or |A| For 1 x 1 matrices: det( [k] ) = k.
Economics 2301 Matrices Lecture 12. Inner Product Let a' be a row vector and b a column vector, both being n-tuples, that is vectors having n elements:
Chapter 3 Determinants 3.1 The Determinant of a Matrix
Economics 2301 Matrices Lecture 13.
4.III. Other Formulas 4.III.1. Laplace’s Expansion Definition 1.2:Minor & Cofactor For any n  n matrix T, the (n  1)  (n  1) matrix formed by deleting.
Matrices and Determinants
Determinants King Saud University. The inverse of a 2 x 2 matrix Recall that earlier we noticed that for a 2x2 matrix,
Recall that a square matrix is one in which there are the same amount of rows as columns. A square matrix must exist in order to evaluate a determinant.
Mathematics.
Spring 2013 Solving a System of Linear Equations Matrix inverse Simultaneous equations Cramer’s rule Second-order Conditions Lecture 7.
Chapter 2 Determinants. The Determinant Function –The 2  2 matrix is invertible if ad-bc  0. The expression ad- bc occurs so frequently that it has.
Chapter 4 Matrices By: Matt Raimondi.
1 © 2010 Pearson Education, Inc. All rights reserved © 2010 Pearson Education, Inc. All rights reserved Chapter 9 Matrices and Determinants.
Ch X 2 Matrices, Determinants, and Inverses.
1 Ch. 4 Linear Models & Matrix Algebra Matrix algebra can be used: a. To express the system of equations in a compact manner. b. To find out whether solution.
Matrices CHAPTER 8.1 ~ 8.8. Ch _2 Contents  8.1 Matrix Algebra 8.1 Matrix Algebra  8.2 Systems of Linear Algebra Equations 8.2 Systems of Linear.
Algebra 2 Chapter 4 Notes Matrices & Determinants Algebra 2 Chapter 4 Notes Matrices & Determinants.
4.3 Matrices and Determinants Algebra 2. Learning Targets: Evaluate the determinant of a 3 x 3 matrix, and Find the area of a triangle given the coordinates.
Chapter 3 Determinants Linear Algebra. Ch03_2 3.1 Introduction to Determinants Definition The determinant of a 2  2 matrix A is denoted |A| and is given.
Justin Gilmore Problem Set 1- #15 15.If r is the rank and d is the determinant of the matrix what is r-d? In order to solve the problem, we must first.
Sec 3.6 Determinants 2x2 matrix Evaluate the determinant of.
Chapter 2 Determinants. With each square matrix it is possible to associate a real number called the determinant of the matrix. The value of this number.
4-5 – 2x2 Matrices, Determinants, & Inverses. Objectives Evaluating Determinants of 2x2 Matrices Using Inverse Matrices to Solve Equations.
Copyright © Cengage Learning. All rights reserved. 7.7 The Determinant of a Square Matrix.
Matrix Multiplication The Introduction. Look at the matrix sizes.
LEARNING OUTCOMES At the end of this topic, student should be able to :  D efination of matrix  Identify the different types of matrices such as rectangular,
Section 2.1 Determinants by Cofactor Expansion. THE DETERMINANT Recall from algebra, that the function f (x) = x 2 is a function from the real numbers.
Copyright © 1999 by the McGraw-Hill Companies, Inc. Barnett/Ziegler/Byleen College Algebra, 6 th Edition Chapter Seven Matrices & Determinants.
Matrix – is a rectangular arrangement of numbers in rows and columns. Dimensions – Size – m is rows, n is columns. m x n ( row ∙ column) Elements – The.
Chapter 5: Matrices and Determinants Section 5.1: Matrix Addition.
Copyright © 2001 by the McGraw-Hill Companies, Inc. Barnett/Ziegler/Byleen Precalculus: Functions & Graphs, 5 th Edition Chapter Nine Matrices & Determinants.
Slide INTRODUCTION TO DETERMINANTS Determinants 3.1.
MATH 1046 Determinants (Section 4.2)
Matrices Introduction.
Sec 3.6 Determinants 2x2 matrix Evaluate the determinant of.
nhaa/imk/sem /eqt101/rk12/32
Matrices.
CHAPTER 2 MATRICES Determinant Inverse.
Determinants by Dr. Shorouk Ossama.
3.1 Introduction to Determinants
Finding the Inverse of a Matrix
Barnett/Ziegler/Byleen College Algebra, 7th Edition
DETERMINANTS A determinant is a number associated to a square matrix. Determinants are possible only for square matrices.
Copyright © Cengage Learning. All rights reserved.
4.3 Determinants & Cramer’s Rule
Chapter 2 Determinants by Cofactor Expansion
Fundamentals of Engineering Analysis
Instructor: Irvin Roy Hentzel Office 432 Carver Phone
Linear Algebra Lecture 17.
DETERMINANT MATRIX YULVI ZAIKA.
3.2 Properties of Determinants
MATRIX 1.
9-5 Higher Order Determinants
Section 2.4 Matrices.
3.2 Properties of Determinants
Matrices Introduction.
Definition of Cofactors
3.7 Evaluate Determinants & Apply Cramer’s Rule
The Determinant of a 2  2 Matrix
Systems of linear equations:
Matrices and Determinants
Chapter 2 Determinants.
Chapter 2 Determinants.
Matrices - Operations ADJOINT MATRICES
L4-5/L4-6 Objective: Students will be able to evaluate determinants of matrices.
Presentation transcript:

Section 8.4: Determinants Definition of Cofactors

Definition of Cofactors Let M = The cofactor of the i-th row and the j-th column is defined by Aij = (-1)i + j(2 x 2 determinant obtained by deleting the i-th row and the j-th column)

Definition of Cofactors Let M = The cofactor of the i-th row and the j-th column is defined by Aij = (-1)i + j(2 x 2 determinant obtained by deleting the i-th row and the j-th column)

Definition of Cofactors Let M = The cofactor of the i-th row and the j-th column is defined by Aij = (-1)i + j(2 x 2 determinant obtained by deleting the i-th row and the j-th column)

Relation between Cofactors and Determinants Let M = det M = aei + bfg + cdh – ceg – afh – bdi Expansion along the 1st row

Expansion along the 2nd row Let M = det M = aei + bfg + cdh – ceg – afh – bdi Expansion along the 2nd row

Expansion along the columns Expansion along the 1st column What should be the value of bA11 + eA21 + hA31? e h b C1 – C2 = 0 Similarly, aA21 + bA22 + cA23 = 0.

Applications = (a + a’)A11 + (d + d’)A21 + (g + g’)A31 = (aA11 + dA21 + gA31) + (a’A11 + d’A21 + g’A31) Why?

Adjoint Matrix Let M = The adjoint matrix of M is defined by adj M =

The product of M and adj M M(adj M) = det M Expansion along the first row

The product of M and adj M M(adj M) = det M Expansion along the second row det M det M

The product of M and adj M M(adj M) = dA21 + eA22 + fA23 = det M, but aA21 + bA22 + cA23 = 0. det M det M det M

The product of M and adj M M(adj M) = gA31 + hA32 + iA33 = det M, but aA31 + bA32 + cA33 = 0. det M = (det M)I det M det M

Conclusion Let M be a square matrix. Then M(adj M) = (adj M)M = (det M)I. If det M  0, then