Program for Matrix Analysis
clc
close all
clear all
% A = [1 -2i; 1i -2]; % Given matrix
A = [1 2 3; 0 1 5; 5 6 0]
detA = det(A); %
Determinant
fprintf('The
determinant is:\n');
disp(detA);
%% Check for singularity with conditional statement
if
detA == 0
fprintf('The
given matrix is singular\n');
else
fprintf('The
given matrix is non singular\n');
end
%% Check for orthogonality with conditional statement
if
detA == 1 || detA == -1
fprintf('The
given matrix is orthogonal\n');
else
fprintf('The
given matrix is non orthogonal\n');
end
invA = inv(A); %
Inverse
fprintf('The
inverse is:\n');
disp(invA);
transA = transpose(A); % Transpose
fprintf('The
transpose is:\n');
disp(transA);
squareA = A*A; %
Square value of matrix
fprintf('The
square of given matrix is:\n');
disp(squareA);
%% Eigne values and Eigne vectors
eigVal = eig(A); %
Eigen values
fprintf('The
eigen values are:\n');
disp(eigVal);
% or
[V D] = eig(A); %
Eigen vectors and eigen velues
fprintf('The
eigen vector and eigen values are:\n');
disp(V);
disp(D);
%% Rank
rankA = rank(A);
fprintf('The
rank is:\n');
disp(rankA);
A =
1 2 3
0 1 5
5 6 0
The determinant is:
5.0000
The given matrix is non singular
The given matrix is non orthogonal
The inverse is:
-6.0000 3.6000 1.4000
5.0000 -3.0000 -1.0000
-1.0000 0.8000 0.2000
The transpose is:
1 0 5
2 1 6
3 5 0
The square of given matrix is:
16 22 13
25 31 5
5 16 45
The eigen values are:
-5.6418
-0.1143
7.7561
The eigen vector and eigen values are:
0.1769 -0.7592 -0.4704
0.5919 0.6353 -0.5250
-0.7863 -0.1416 -0.7093
-5.6418 0 0
0 -0.1143 0
0 0 7.7561
The rank is:
3
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