I don’t have your data, so I created my own:
zci = @(v) find(v(:).*circshift(v(:), [-1 0]) <= 0); % Returns Zero-Crossing Indices Of Argument Vector
x = linspace(0, 100, 250); % Independent Variable
y1 = exp(-0.05*x).*sin(2*pi*x/30); % First Dependent Variable
y2 = 0.5*exp(-0.07*x).*sin(2*pi*x/20); % Second Dependent Variable
yd = y1 - y2; % Difference (Use To Detect Zero-Crossings)
xc = zci(yd); % Zero Crossings
idxs = xc(2:2:end-1); % Start Indices Of Overlap
idxe = xc(3:2:end); % End Indices Of Overlap
figure(1)
plot(x, y1)
hold on
plot(x, y2)
for k1 = 1:size(idxs,1)
fill([x(idxs(k1):idxe(k1)) fliplr(x(idxs(k1):idxe(k1)))], [y1(idxs(k1):idxe(k1)) fliplr(y2(idxs(k1):idxe(k1)))], 'g')
end
hold off
grid
You should be able to adapt it to your data with little or no alteration, although you might need to adjust ‘idxs’ and ‘idxe’.
