hello
this is a little demo you can adapt to your own needs ...
clc
clearvars
close all
% dummy signal (sinus + noise)
dt = 1e-4;
samples = 1000;
f = 50;
t = (0:samples-1)*dt;
s = 0.75*sin(2*pi*f*t) + 0.1 *rand(1,samples);
%%%%%%%%%%%%% main code %%%%%%%%%%%%%%%%%
ym = mean(s); % Estimate offset
yu = max(s);
yl = min(s);
yr = (yu-yl); % Range of ‘y’
yz = s-ym;
yzs = smoothdata(yz,'gaussian',25); % smooth data to remove noise artifacts (adjust factors)
zt = t(yzs(:) .* circshift(yzs(:),[1 0]) <= 0); % Find zero-crossings
per = 2*mean(diff(zt)); % Estimate period
fre = 1/per; % Estimate FREQUENCY
% stationnary sinus fit
fit = @(b,x) b(1) .* (sin(2*pi*x*b(2) + b(3))) + b(4); % Objective Function to fit
fcn = @(b) norm(fit(b,t) - s); % Least-Squares cost function
B = fminsearch(fcn, [yr/2; fre; 0; 0;]); % Minimise Least-Squares
amplitude = B(1)
frequency_Hz = B(2)
phase_rad = B(3)
DC_offset = B(4)
xp = linspace(min(t),max(t),samples);
yp = fit(B,xp);
figure(1),
plot(t, s, 'db',xp, yp, '-r')
legend('data + noise','model fit');
