uncertainty analysis in matlab in matlab

In MATLAB, you can perform uncertainty analysis using the "Symbolic Math Toolbox" which allows you to define symbolic variables with uncertainties and propagate them through mathematical expressions.

Here is a simple example to demonstrate uncertainty analysis in MATLAB:

main.m
% Define symbolic variables with uncertainties
syms x y
assume (x, 'real');  % assuming x to be real
mu_x = 3;  % mean
sigma_x = 0.1;  % standard deviation
mean_x = sym('mu_x', 'real');
var_x = sigma_x^2;

assume (y, 'real');  % assuming y to be real
mu_y = 4;
sigma_y = 0.2;
mean_y = sym('mu_y', 'real');
var_y = sigma_y^2;

% Define a mathematical expression
z = x + y;

% Propagate uncertainties
mean_z = mean(z);
var_z = var(z);
std_dev_z = sqrt(var_z);

% Display results
disp(['Mean of z: ' char(mean_z)]);
disp(['Variance of z: ' char(var_z)]);
disp(['Standard Deviation of z: ' char(std_dev_z)]);
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In this example, we define two symbolic variables x and y with corresponding mean and standard deviation. Then, we define a mathematical expression z as the sum of x and y. Finally, we calculate the mean, variance, and standard deviation of z by propagating the uncertainties through the expression.

You can extend this example to more complex mathematical expressions and multiple variables.