Hi Gulzar,
It seems like you are trying to perform matrix multiplication for a layered medium simulation, where the thickness of each layer is determined by a normal distribution. You want to generate 20 output values corresponding to the number of samples in your normal distribution matrix ('d1'), for a given set of 'x' values.
However, your code calculates 'fx' for each value of 'x' in the loop but overwrites it in each iteration, and the final 'disp(fx)' only shows the last computed value of 'fx'.
To achieve 20 distinct output values corresponding to each column in your 'd1' matrix (each sample), you need to adjust your approach as shown below:
clc
clear
close all
x = pi:0.01:2*pi;
mu = 25;
sigma = 1.5;
n = 10;
num_samples = 20;
d0 = 25;
d1 = normrnd(mu, sigma, [n, num_samples]);
% Initialize an array to store the output values of fx for each sample
fx_values = zeros(1, num_samples);
% Loop over each sample
for sample = 1:num_samples
Fy = eye(2); % Initialize total matrix as identity for layer 2
for i = 1:length(x)
x_value = x(i);
X1 = x_value * d0;
Fx = [sin(X1) 1i; -1i cos(X1)];
% Reset Fy for each x value
Fy = eye(2);
for j = 1:n
X2 = x_value * d1(j, sample);
M = [sin(X2) 1i; -1i cos(X2)];
Fy = Fy * M; % Update Fy for each layer
end
Fxx = (Fx^n * Fy);
fx = Fxx(1,1) + Fxx(2,2);
end
% Store the last computed fx value for this sample
fx_values(sample) = fx;
end
disp(fx_values)
In the above code, 'fx_values' stores the final 'fx' value for each sample. This is necessary because you want 20 distinct outputs corresponding to your 'num_samples'.
