I would like to add Gaussian noise Model with variable Standard Deviation (Sigma) and Variable Mean (Mu) to my Output Curve which is shown in the figure below
http://i.imgur.com/hABfsiC.jpg
Following function generates the Output curve expressed in the figure above
function c_t = output_function_constrainedK2(t, a1, a2, a3,b1,b2,b3,td, tmax,k1,k2,k3)
K_1 = (k1*k2)/(k2+k3);
K_2 = (k1*k3)/(k2+k3);
DV_free= k1/(k2+k3);
c_t = zeros(size(t));
ind = (t > td) & (t < tmax);
c_t(ind)= conv(((t(ind) - td) ./ (tmax - td) * (a1 + a2 + a3)),(K_1*exp(-(k2+k3)*t(ind)+K_2)),'same');
ind = (t >= tmax);
c_t(ind)= conv((a1 * exp(-b1 * (t(ind) - tmax))+ a2 * exp(-b2 * (t(ind) - tmax))) + a3 * exp(-b3 * (t(ind) - tmax)),(K_1*exp(-(k2+k3)*t(ind)+K_2)),'same');
plot(t,c_t);
axis([0 50 0 1400]);
xlabel('Time[mins]');
ylabel('concentration [Mbq]');
title('Model :Constrained K2');
end
The output values for the above function are
output_function_constrainedK2(0:0.1:50,2501,18500,65000,0.5,0.7,0.3,...
0.28,0.9,0.014,0.051,0.07)
Now i would like to add the Gaussian probability distribution function with variable Standard deviation Sigma and mean to the above function, could any one please help me through this , I am an absolute beginner to matlab