MLA Runge Katta

An Approach to Matrix & Linear Algebra

by Frank C. Fung ( 1st published in November, 2004. )

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Appendix A : The Runge Katta Method for a { 3 x 3 matrix } :

Topic IIntroduction & Summary for this Appendix.
Topic IIThe Set of { 3 Linear Equations }
Topic IIIThe Runge Katta Method in action
Topic IVAn Analysis of the { Determinant }

Topic I - Introduction & Summary for this Appendix :

The Runge Katta Method is a numerical method / procedure that provides a solution to a given set of { Linear Equations }.

This Appendix then runs thru the Runge Katta Method for a { 3 x 3 } matrix .

The [ Determinant ] for the general { 3 x 3 } [ Solution Matrix ] is also analysed with interesting results.

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Topic II - The set of { 3 Linear Equations } :

Let us now start out with this set of { 3 Linear Equations } and try to solve for the values of 'X' , 'Y' , & 'Z' .

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Topic III - The Runge Katta Method in action :

We shall now proceed to use the { Runge Katta Method } to arrive at the solution.

1st pass :

We then divide the { 1st row } by [ A ] to arrive at the 'equivalent' { matrix equation } :

2nd pass :

We then :

to arrive at :

yielding :

3rd pass :

We then divide the { 2nd row } by { [ A*E - B*D ] / A } to arrive at the 'equivalent' { matrix equation }:

4th pass :

We then :

to arrive at :

yielding :

5th pass :

We then divide the { 3rd row } by :

6th & final pass :

We then :

to arrive at :

Expanding and consolidating terms then yields :

where :

We can then write :

or simply :

Thus, for any given set of values for '' , '' , & '' , we can always find a set of values for 'X' , 'Y', & 'Z' via the [ equation for the solution ] presented here immediately above.

And we shall call this :

the [ Solution Matrix ] .

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Topic IV - An anylysis of the { Determinant } :

Let us now define the { Matrix [ W ] } as follows :

We can then write the above { equation for the solution } , in this format below :

Let us now look at the { Determinant } for the { Matrix [ W ] } .

And we introduce this table below, for { Matrix [ W ] } , for better clarity :

COLUMN-1 COLUMN-2 COLUMN-3
ROW-1 E*J - F*H C*H - B*J B*F - C*E
ROW-2 F*G - D*J A*J - C*G C*D - A*F
ROW-3 D*H - E*G B*G - A*H A*E - B*D

The [ Determinant ] for this { 3 x 3 } matrix has six (6) terms :

1st term : ( +1 ) * ( E*J - F*H ) * ( A*J - C*G ) * ( A*E - B*D )
2nd term : ( +1 ) * ( C*H - B*J ) * ( C*D - A*F ) * ( D*H - E*G )
3rd term : ( +1 ) * ( B*F - C*E ) * ( F*G - D*J ) * ( B*G - A*H )
4th term : ( -1 ) * ( E*J - F*H ) * ( C*D - A*F ) * ( B*G - A*H )
5th term : ( -1 ) * ( C*H - B*J ) * ( F*G - D*J ) * ( A*E - B*D )
6th term : ( -1 ) * ( B*F - C*E ) * ( A*J - C*G ) * ( D*H - E*G )

We then have this calculation table below for the expansion :

{ square }
terms
{ non-square }
terms
A
A
E
E
J
J
A
A
F
F
H
H
B
B
D
D
J
J
B
B
F
F
G
G
C
C
D
D
H
H
C
C
E
E
G
G
A
A
E
F
H
J
A
B
D
E
J
J
A
B
D
F
H
J
A
B
E
F
G
J
A
B
F
F
G
H
A
C
D
E
H
J
A
C
D
F
H
H
A
C
E
E
G
J
A
C
E
F
G
H
B
B
D
F
G
J
B
C
D
D
H
J
B
C
D
E
G
J
B
C
D
F
G
H
B
C
E
F
G
G
C
C
D
E
G
H
1st term +1 -1-1+1 -1+1 +1-1
2nd term +1 +1-1 -1+1 -1+1-1
3rd term +1 +1-1-1 +1 -1+1-1
4th term +1 -1+1-1+1 -1 -1+1
5th term +1 -1+1+1 -1 -1-1+1
6th term +1 -1+1+1 -1 +1-1-1
--------- --------- --------- --------- --------- --------- ---------
SUM of terms +1+1+1+1+1+1 -2-2+2+2-2+2 -2-2+2 -2-2+2+2-2-2

We simply note here that :

Let us now look at the [ Determinant ] for the { 3 x 3 } [ Solution Matrix ] .

We then have this relation below :

This is because :

so that the net effect is that :

We then have :

( This then also set the stage for "normalizing the Determinant", for a { 4 x 4 Matrix } and so-on-and-so-forth , should it become desirable to do so .)

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original dated 2004-11-15