(Part A) Machinerys Handbook 31st Edition Pages 1-1484

Machinery's Handbook, 31st Edition

126

Matrix Operations

4 6 3 1

4 1 ( × )

6 3 ( × ) –

=

=

=

4– 18 –14 =

M 12

Continuing this way, we obtain the following minors: M 11 = –7 M 12 = –14

M 13 = –7 M 23 = –4 M 33 = –3

M 21 = –4 M 31 = –3

M 22 = –8 M 32 = –6 ( i + j ) × M

To find the cofactor, calculate C ij = ( - 1) Similarly C 12 = ( - 1) (1+2) × M

ij , thus C 11 = ( - 1)

11 = 1 × ( - 7) = - 7.

(1+1) × M

12 = ( - 1)( - 14) = 14, and continuing this way we obtain the

following cofactors

C 11 = –7 C 21 = 4 C 31 = –3

C 12 = 14 C 22 = –8 C 32 = 6

C 13 = –7 C 23 = 4 C 33 = –3

–7 14 –7

Thus, the cofactor matrix is

4 –8 4

–3 6 –3 Adjoint of a Matrix.— The transpose of cofactor matrix is called the adjoint matrix. To obtain the adjoint matrix, the cofactor matrix is determined and then transposed. Example 7: Find the adjoint matrix of A :

1 2 3 4 5 6 3 2 1

=

A

Solution: The cofactor matrix from the above example is shown below at the left, and the adjoint matrix is shown on the right.

T

–7 14 –7 4 –8 4 –3 6 –3

–7 14 –7 4 –8 4 –3 6 –3

–7 4 –3 14 –8 6 –7 4 –3

cofactor A ( )

adj A ( )

=

=

=

Singularity and Rank of a Matrix.— A singular matrix is one whose determinant is zero. The rank of a matrix is the maximum number of linearly independent row or column vectors it contains. In ALGEBRA , Solving a System of Linear Equations , it is explained that a system with a unique solution is a linearly independent system. Such systems are vital to depicting many real-life processes. Dependent systems are those with infinite solutions (the lines are collinear), and their determinant is zero. Linearly independent vectors have a non-zero determinant. Inverse of a Matrix.— A square non-singular matrix A has an inverse A - 1 such that the product of matrix A and inverse matrix A - 1 is the identity matrix I . The operation is com- mutative as well. Thus, AA - 1 = A - 1 A = I . The inverse is the ratio of adjoint of the matrix and the determinant of that matrix. A –1 adj A ( ) A = -------- Example 8: What is the inverse of the following matrix?

2 3 5 4 1 6 1 4 0

=

A

Solution: The basic formula of an inverse of a matrix is A –1 adj A ( ) A = --------

Copyright 2020, Industrial Press, Inc.

ebooks.industrialpress.com

Made with FlippingBook - Share PDF online