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Note on the Generalized Inverse of a Matrix Product

NOTE ON THE GENERALIZED INVERSE OF A MATRIX PRODUCT*. T. N. E. GREVILLEt. It is well known that the Moore-Penrose generalized inverse of a matrix.



Matrix inversion Math 130 Linear Algebra

and that A is an inverse of B. If a matrix has no The inverse of an invertible matrix is ... follows from associativity of matrix multiplication.



Note on the Generalized Inverse of a Matrix Product

NOTE ON THE GENERALIZED INVERSE OF A MATRIX PRODUCT*. T. N. E. GREVILLE. It is well known that the Moore-Penrose generalized inverse of a matrix.



2.5 Inverse Matrices

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A Hyperpower Iterative Method for Computing Matrix Products

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Vector - matrix multiplication is defined as for matrix - matrix The inverse of the product of two matrices is the reversed product of the inverses:.



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Nov 7 2003 Key Words and phrases. Mixed-type reverse-order law



The Forward Order Law for Least Squareg-Inverse of Multiple Matrix

Mar 19 2019 Keywords: forward order law; generalized inverse; maximal rank; matrix product; generalized Schur complement. 1. Introduction.



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Diagonal matrices. Inverse matrix. Scalar multiplication: to multiply a matrix A by ... The product of matrices A and B is defined if the.



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In this leaflet we explain what is meant by an inverse matrix and how the inverse of a 2 × 2 matrix is calculated Preliminary example Suppose we calculate the 



[PDF] Matrices transposes and inverses

1 fév 2012 · This is a requirement in order for matrix multiplication to be defined The notion of an inverse matrix only applies to square matrices



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The following examples will show a method to solve for the inverse of a matrix Example 1: Find the inverse of the matrix 1 4 1 3 A ? ?



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The idea is the Inverse Criterion: If a matrix B can be found such that AB = I = BA then A is invertible and A?1 = B Example 2 4 8 If A is an invertible 



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The product of the two matrices is indeed the identity matrix so we're done Linear Systems and Inverses If M?1 exists and is known then we can immediately 



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We can add two matrices of the same size just by adding their components We can multiply a matrix by a scalar just by multiplying each entry by that 



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We will also show somewhat surprisingly that one can also compute the inverse of a matrix with a number of compu- tations that is not markedly different from 



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and that A is an inverse of B If a matrix has no The inverse of an invertible matrix is follows from associativity of matrix multiplication



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Inverse for matrix product • A and B are invertible nxn matrices is AB invertible? • Let 1 2 ? be nxn invertible matrices The product



[PDF] Lecture 6 Inverse of Matrix

Left-multipling the matrix equation by the inverse matrix C = A-1 we have Multiplying the above equation by B from the left we find B (BC) = BI2

  • What is the inverse of a matrix product?

    5. inverse of a matrix product: inv(A * B) = inv(B) %*% inv(A) This extends to any number of terms: the inverse of a product is the product of the inverses in reverse order.
  • What is inverse product?

    Let A,B?Fn×n where F denotes a field and n is a positive integer. Let C=AB. If A and B are both invertible, then C is invertible and C?1 is given by B?1A?1. (
  • How to find the inverse of a matrix as a product of elementary matrices?

    In fact, the inverse of an elementary matrix is constructed by doing the reverse row operation on I. E?1 will be obtained by performing the row operation which would carry E back to I. If E is obtained by switching rows i and j, then E?1 is also obtained by switching rows i and j.
  • What is the Inverse of 3x3 Matrix? The inverse of a 3x3 matrix, say A, is a matrix of the same order denoted by A-1 where AA-1 = A-1A = I, where I is the identity matrix of order 3x3. i.e., I = ???100010010??? [ 1 0 0 0 1 0 0 1 0 ] .

Matrices, transposes, and inverses

Math 40, Introduction to Linear Algebra

Wednesday, February 1, 2012

1-23 215
4 3 2 4 dotproduct of 2 1 5 and 4 3 2 4 21

Matrix-vector multiplication: two views

1-23 215
4 3 2 =4 1 2 +3 -2 1 +2 3 5 A

1st perspective: A is linear combination of columns of A

?x?x

2nd perspective: A is computed as dot product of rows of A with vector

?x?x

Notice that # of columns of A = # of rows of .

This is a requirement in order for matrix multiplication to be defined. ?x A ?x 1-23 215
4 3 2 =4 1 2 +3 -2 1 +2 3 5 4 21
"inner" parameters must match m x n n x p

Matrix multiplication

For m x n matrix A and n x p matrix B,

the matrix product AB is an m x p matrix. "outer" parameters become parameters of matrix AB What sizes of matrices can be multiplied together? If A is a square matrix and k is a positive integer, we define A k =A·A···A kfactors

Properties of matrix multiplication

Most of the properties that we expect to hold for matrix multiplication do.... A(B+C)=AB+AC(AB)C=A(BC)k(AB)=(kA)B=A(kB)for scalark .... except commutativity!!

In general,

AB?=BA.

Matrix multiplication not commutative

In general,

AB?=BA.

Problems with hoping AB and BA are equal:

BA may not be well-defined.

Even if AB and BA are both defined, AB and BA may not be the same size. Even if AB and BA are both defined and of the same size, they still may not be equal. (e.g., A is 2 x 3 matrix, B is 3 x 5 matrix)(e.g., A is 2 x 3 matrix, B is 3 x 2 matrix) 11 11 12 12 12 12 11 11 33
33
24
24

Truth or fiction?

For n x n matrices A and B, is

Question 1

A 2 -B 2 =(A-B)(A+B)?

Question 2

For n x n matrices A and B, is

(AB) 2 =A 2 B 2

No!!No!!

(A-B)(A+B)=A 2 +AB-BA-B 2 AB-BA ?=0 (AB) 2 =ABAB?=AABB=A 2 B 2

Matrix transpose

A T 15 33
52
-21 A= 135-2
5321

Example

Transpose operation can be viewed as

flipping entries about the diagonal. i.e.,(A T ij =A ji ?i,j. Definition The transpose of an m x n matrix A is the n x m matrix A T obtained by interchanging rows and columns of A, Definition A square matrix A is symmetric if A T = A.

Properties of transpose

(1) (A T T =A (2) (A+B) T =A T +B T (3)

Forascal arc,(cA)

T =cA T (4) (AB) T =B T A T

To prove this, we show that

[(AB) T ij =[(B T A T ij apply twice -- get back to where you started

ExerciseProve that for any matrix A, A

T

A is symmetric.

Special matrices

Definition A square matrix is upper-triangular if all entries below main diagonal are zero. A= 2 1 4 5 060
00-3 Definition A matrix with all zero entries is called a zero matrix and is denoted 0. A= 0000 0000 0000 analogous definition for a lower-triangular matrix Definition A square matrix whose off-diagonal entries are all zero is called a diagonal matrix. A= 3 8 000 0-200 00-40 0001 Definition The identity matrix, denoted I n , is the n x n diagonal matrix with all ones on the diagonal. I 3 100
010 001

Identity matrix

Definition The identity matrix, denoted I n , is the n x n diagonal matrix with all ones on the diagonal. I 3 100
010 001

Important property

of identity matrix

If A is an m x n matrix, then

I m

A = A and AI

n = A.

If A is a square matrix, then

IA = A = AI.

The notion of inverse

Consider the set of real numbers, and say that we have the equationquotesdbs_dbs20.pdfusesText_26
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