hello
see my little demo below. I assumed that you would split the rms data in 3 groups corresponding to ranges
- 0 to 33% of max rms
- 33 to 66% of max rms
- above 66% of max rms
the 3 groups are the colored dots
code :
clearvars
% dummy data
n=300;
x=linspace(0,2*pi,n);
data = 0.25*ones(size(x));
data = max(data,-cos(x));
buffer = 10; % nb of samples in one buffer (buffer size)
overlap = 5; % overlap expressed in samples
%%%% main loop %%%%
m = length(data);
shift = buffer-overlap; % nb of samples between 2 contiguous buffers
for ci=1:fix((m-buffer)/shift +1)
start_index = 1+(ci-1)*shift;
stop_index = min(start_index+ buffer-1,m);
time_index(ci) = round((start_index+stop_index)/2); % time index expressed as sample unit (dt = 1 in this simulation)
rms_data(ci) = my_rms(data(start_index:stop_index)); %
end
x_rms = x(time_index);
figure(1),
plot(x,data,x_rms,rms_data,'r*');
%select index if they belong to ranges : 0 - 33% of max / 33 - 66% of max / above 66% of max
ind1 = find(rms_data<=max(rms_data)/3); % range : 0 - 33% of max
ind2 = find(rms_data>max(rms_data)/3 & rms_data<=max(rms_data)*2/3); % range : 33 - 66% of max
ind3 = find(rms_data>max(rms_data)*2/3); % range : above 66% of max
figure(1),
plot(x,data,'k',x_rms(ind1),rms_data(ind1),'g*',x_rms(ind2),rms_data(ind2),'b*',x_rms(ind3),rms_data(ind3),'r*');
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function x_rms = my_rms(x)
x_rms = sqrt(mean(x.^2));
end
