334 CHAPTER 14. NUMERICAL SOLUTIONS OF LINEAR SYSTEMS

sequence of vectors will converge to the solution to 14.1. The vectors in this list are callediterates and they are obtained according to the following procedure. Letting A = (ai j) ,

aiixr+1i =−∑

j ̸=iai jxr

j +bi. (14.2)

In terms of matrices, letting

A =

a11 · · · a1n

.... . .

...an1 · · · ann

The iterates are defined as

a11 0 · · · 0

0 a22. . .

......

. . .. . . 0

0 · · · 0 ann



xr+11

xr+12...

xr+1n



= −

0 a12 · · · a1n

a21 0. . .

......

. . .. . . an−1n

an1 · · · ann−1 0



xr1

xr2...

xrn

+

b1

b2...

bn

 (14.3)

If these iterates do converge, then the vector to which they converge will be a solution tothe original system of equations.

The matrix on the left in 14.3 is obtained by retaining the main diagonal of A and settingevery other entry equal to zero. The matrix on the right in 14.3 is obtained from A by settingevery diagonal entry equal to zero and retaining all the other entries unchanged.

Example 14.1.4 Use the Jacobi method to solve the system3 1 0 01 4 1 00 2 5 10 0 2 4



x1

x2

x3

x4

=

1234

In terms of the matrices, the Jacobi iteration is of the form

3 0 0 00 4 0 00 0 5 00 0 0 4



xr+11

xr+12

xr+13

xr+14

=−

0 1 0 01 0 1 00 2 0 10 0 2 0



xr1

xr2

xr3

xr4

+

1234

 .