Methid For find Inverse 15 Elementary Matrices and a Method for Finding A 1 Linear Algebra Chapter 1 3 Elementary Matrices Definition An n x n matrix is called an elementary matrix if it can be obtained from the ID: 1022249
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1. Lecture 5 Elementary Matrix MethidFor findInverse
2. 1.5 Elementary Matrices and a Method for Finding A-1
3. Linear Algebra - Chapter 13Elementary MatricesDefinition:An n x n matrix is called an elementary matrix if it can be obtained from the n x n identity matrix In by performing a single elementary row operation.Example:Multiply the second row of I2 by -3.Interchange the second and fourth rows of I4.Add 3 times the third row of I3 to the first row.
4. Linear Algebra - Chapter 14Elementary MatricesTheorem: (Row Operations by Matrix Multiplication)If the elementary matrix E results from performing a certain row operation on Im and if A is an m x n matrix, then the product of EA is the matrix that results when this same row operation is performed on A.Example:EA is precisely the same matrix that results when we add 3 times the first row of A to the third row.
5. Linear Algebra - Chapter 15Elementary MatricesIf an elementary row operation is applied to an identity matrix I to produce an elementary matrix E, then there is a second row operation that, when applied to E, produces I back again.Inverse operationRow operation on I that produces ERow operation on E that reproduces IMultiply row i by c ≠ 0Multiply row i by 1/cInterchange rows i and jInterchange rows i and jAdd c times row i to row jAdd –c times row i to row j
6. Linear Algebra - Chapter 16Elementary MatricesTheorem: Every elementary matrix is invertible, and the inverse is also an elementary matrix.Theorem: (Equivalent Statements)If A is an n x n matrix, then the following statements are equivalent, that is, all true or all false.A is invertibleAx = 0 has only the trivial solution.The reduced row-echelon form of A is In.A is expressible as a product of elementary matrices.
7. Linear Algebra - Chapter 17Elementary MatricesProof: Assume A is invertible and let x0 be any solution of Ax=0. Let Ax=0 be the matrix form of the system
8. Linear Algebra - Chapter 18Elementary Matrices Assumed that the reduced row-echelon form of A is In by a finite sequence of elementary row operations, such that: By theorem, E1,…,En are invertible. Multiplying both sides of equation on the left we obtain: This equation expresses A as a product of elementary matrices. If A is a product of elementary matrices, then the matrix A is a product of invertible matrices, and hence is invertible.Matrices that can be obtained from one another by a finite sequence of elementary row operations are said to be row equivalent.An n x n matrix A is invertible if and only if it is row equivalent to the n x n identity matrix.
9. Linear Algebra - Chapter 19A Method for Inverting MatricesTo find the inverse of an invertible matrix, we must find a sequence of elementary row operations that reduces A to the identity and then perform this same sequence of operations on In to obtain A-1.Example:Adjoin the identity matrix to the right side of A, thereby producing a matrix of the form [A|I]Apply row operations to this matrix until the left side is reduced to I, so the final matrix will have the form [I|A-1].
10. Linear Algebra - Chapter 110A Method for Inverting Matrices Added –2 times the first row to the second and –1 times the first row to the third. Added 2 times the second row to the third. Multiplied the third row by –1. Added 3 times the third row to the second and –3 times the third row to the first. We added –2 times the second row to the first.
11. Linear Algebra - Chapter 111A Method for Inverting MatricesOften it will not be known in advance whether a given matrix is invertible.If elementary row operations are attempted on a matrix that is not invertible, then at some point in the computations a row of zeros will occur on the left side.Example: Added -2 times the first row to the second and added the first row to the third. Added the second row to the third.
12. Linear Algebra - Chapter 112ExercisesConsider the matrices Find elementary matrices, E1, E2, E3, and E4, such thatE1A=BE2B=AE3A=CE4C=A
13. Linear Algebra - Chapter 113ExercisesExpress the matrix: in the form A = E F G R, where E, F, G are elementary matrices, and R is in row-echelon form.
14. 1.6 Further Results on Systems of Equations and Invertibility
15. Linear Algebra - Chapter 115Linear SystemsTheorem: Solving Linear Systems by Matrix Inversion: If A is an invertible n x n matrix, then for each n x 1 matrix b, the system of equations Ax = b has exactly one solution, namely, x = A-1b.Linear systems with a common coefficient matrix.Ax=b1, Ax=b2, Ax=b3, ..., Ax=bkIf A is invertible, then the solutionsx1=A-1b1, x2=A-1b2, x3=A-1b3, ..., xk=A-1bkThis can be efficiently done using Gauss-Jordan Elimination on [A|b1|b2|...|bk]
16. Linear Algebra - Chapter 116Linear SystemsExample: (a) (b) The solution: (a) x1=1, x2=0, x3=1 (b) x1=2, x2=1, x3=-1
17. Linear Algebra - Chapter 117Properties of Invertible MatricesTheorem: Let A be a square matrix.If B is a square matrix satisfying BA=I, then B=A-1.If B is a square matrix satisfying AB=I, then B=A-1.Theorem: Equivalent StatementsA is invertibleAx=0 has only the trivial solutionsThe reduced row-echelon form of A is InA is expresssible as a product of elementary matricesAx=b is consistent for every n x 1 matrix bAx=b has exactly one solution for every n x 1 matrix b
18. Linear Algebra - Chapter 118Properties of Invertible MatricesTheorem: Let A and B be square matrices of the same size. If AB is invertible, then A and B must also be invertible.A fundamental problem. Let A be a fixed m x n matrix. Find all m x 1 matrices b such that the system of equations Ax=b is consistent.
19. Linear Algebra - Chapter 119ExercisesSolve the system by inverting the coefficient matrix.Find condition that b’s must satisfy for the system to be consistent.
20. 1.7 Diagonal, Triangular, and Symmetric Matrices
21. Linear Algebra - Chapter 121Diagonal MatricesA square matrix in which all the entries off the main diagonal are zero. Example:A diagonal matrix is invertible if and only if all of its diagonal entries are nonzero.
22. Linear Algebra - Chapter 122Diagonal MatricesExample:
23. Linear Algebra - Chapter 123Triangular MatricesLower triangular = a square matrix in which all the entries above the main diagonal are zero.Upper triangular = a square matrix in which all the entries under the main diagonal are zero.Triangular = a matrix that is either upper triangular or lower triangular.
24. Linear Algebra - Chapter 124Triangular MatricesTheorem: (basic properties of triangular matrices)The transpose of a lower triangular matrix is upper triangular, and the transpose of an upper triangular matrix is lower triangular.The product of lower triangular matrices is lower triangular, and the product of upper triangular matrices is upper triangular.A triangular matrix is invertible if and only its diagonal entries are all nonzero.The inverse of an invertible lower triangular matrix is lower triangular, and the inverse of an invertible upper triangular matrix is upper triangular.
25. Linear Algebra - Chapter 125Triangular MatricesExample:The matrix A is invertible, since its diagonal entries are nonzero, but the matrix B is not.This inverse is upper triangular. This product is upper triangular.
26. Linear Algebra - Chapter 126Symmetric MatricesA square matrix A is called symmetric if A = AT.A matrix A = [aij] is symmetric if and only if aij=aji for all values of i and j.
27. Linear Algebra - Chapter 127Symmetric MatricesTheorem: If A and B are symmetric matrices with the same size, and if k is any scalar, thenAT is symmetricA+B and A-B are symmetrickA is symmetricTheorem: If A is an invertible matrix, then A-1 is symmetric.If A is an invertible matrix, then AAT and ATA are also invertible.
28. Linear Algebra - Chapter 128ExerciseFind all values of a, b, and c for which A is symmetric.Find all values of a and b for which A and B are both not invertible.