# How do i count the signal within a certain time interval?

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Kwaku Junior on 12 May 2022
Commented: Star Strider on 12 May 2022
the signal shows 1s and 0s. i want to be able to count the 1s with a certain time interval and if it is above a certain figure another signal will show 1 for that time interval.
i want it to go from this to this Star Strider on 12 May 2022
One option is to use the movsum function, and then threshold the result —
t = linspace(0, 100, 100);
s = rand(100,1)>0.80; % Create Pulse Data
ms = movsum(s,[2 2]); % Original
d = movsum(s,[2 2]) >= 3.0; % Using Threshold
figure
stem(t,s,'.')
hold on
plot(t, d, '-r', 'LineWidth',2)
plot(t, ms)
hold off
grid
ylim([0 4])
legend('Pulse Signal','‘movsum’ With Threshold','Original ‘movsum’', 'Location','best') It will likely be necessary for you to refine this to get the result you want.
.
Star Strider on 12 May 2022
As always, my pleasure!

Mathieu NOE on 12 May 2022
hello
below a demo code that look for crossing point between a chirp signal. We detect both the positive and negative slope crossing points (rising / falling signal) and compute the time interval between rising and falling sides
i added a test to show / store only those intervals that comply with min and max values
those points have a black diamond marker on top of the star markers (those shows all crossing points)
the lower subplot is the display of the computed time intervals % dummy data
n=1000;
x= 10*(0:n-1)/n;
y = sin(x.^2);
threshold = max(y)*0.25; % your value here
[t0_pos,s0_pos,t0_neg,s0_neg]= crossing_V7(y,x,threshold,'linear'); % positive (pos) and negative (neg) slope crossing points
% ind => time index (samples)
% t0 => corresponding time (x) values
% s0 => corresponding function (y) values , obviously they must be equal to "threshold"
% periods
period = (t0_neg - t0_pos); % time delta
t_period = (t0_neg + t0_pos)/2; % time value (plot) = mid point
% select valid period values in a range
lower_limit = 0.25;
uper_limit = 0.75;
ind = find(period>=lower_limit & period<=uper_limit);
figure(1)
subplot(2,1,1),plot(x,y,'b',t0_pos,s0_pos,'*r',t0_neg,s0_neg,'*g',t0_pos(ind),s0_pos(ind),'dk',t0_neg(ind),s0_neg(ind),'dk','linewidth',2,'markersize',12);grid on
xlim([min(x) max(x)]);
legend('signal','signal positive slope crossing points','signal negative slope crossing points');
subplot(2,1,2),plot(t_period,period,t_period(ind),period(ind),'dk','linewidth',2,'markersize',12);grid on
xlim([min(x) max(x)]);
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function [t0_pos,s0_pos,t0_neg,s0_neg] = crossing_V7(S,t,level,imeth)
% [ind,t0,s0,t0close,s0close] = crossing_V6(S,t,level,imeth,slope_sign) % older format
% CROSSING find the crossings of a given level of a signal
% ind = CROSSING(S) returns an index vector ind, the signal
% S crosses zero at ind or at between ind and ind+1
% [ind,t0] = CROSSING(S,t) additionally returns a time
% vector t0 of the zero crossings of the signal S. The crossing
% times are linearly interpolated between the given times t
% [ind,t0] = CROSSING(S,t,level) returns the crossings of the
% given level instead of the zero crossings
% ind = CROSSING(S,[],level) as above but without time interpolation
% [ind,t0] = CROSSING(S,t,level,par) allows additional parameters
% par = {'none'|'linear'}.
% With interpolation turned off (par = 'none') this function always
% returns the value left of the zero (the data point thats nearest
% to the zero AND smaller than the zero crossing).
%
% check the number of input arguments
error(nargchk(1,4,nargin));
% check the time vector input for consistency
if nargin < 2 | isempty(t)
% if no time vector is given, use the index vector as time
t = 1:length(S);
elseif length(t) ~= length(S)
% if S and t are not of the same length, throw an error
error('t and S must be of identical length!');
end
% check the level input
if nargin < 3
% set standard value 0, if level is not given
level = 0;
end
% check interpolation method input
if nargin < 4
imeth = 'linear';
end
% make row vectors
t = t(:)';
S = S(:)';
% always search for zeros. So if we want the crossing of
% any other threshold value "level", we subtract it from
% the values and search for zeros.
S = S - level;
% first look for exact zeros
ind0 = find( S == 0 );
% then look for zero crossings between data points
S1 = S(1:end-1) .* S(2:end);
ind1 = find( S1 < 0 );
% bring exact zeros and "in-between" zeros together
ind = sort([ind0 ind1]);
% and pick the associated time values
t0 = t(ind);
s0 = S(ind);
if ~isempty(ind)
if strcmp(imeth,'linear')
% linear interpolation of crossing
for ii=1:length(t0)
%if abs(S(ind(ii))) >= eps(S(ind(ii))) % MATLAB V7 et +
if abs(S(ind(ii))) >= eps*abs(S(ind(ii))) % MATLAB V6 et - EPS * ABS(X)
% interpolate only when data point is not already zero
NUM = (t(ind(ii)+1) - t(ind(ii)));
DEN = (S(ind(ii)+1) - S(ind(ii)));
slope = NUM / DEN;
slope_sign(ii) = sign(slope);
t0(ii) = t0(ii) - S(ind(ii)) * slope;
s0(ii) = level;
end
end
end
% extract the positive slope crossing points
ind_pos = find(sign(slope_sign)>0);
t0_pos = t0(ind_pos);
s0_pos = s0(ind_pos);
% extract the negative slope crossing points
ind_neg = find(sign(slope_sign)<0);
t0_neg = t0(ind_neg);
s0_neg = s0(ind_neg);
else
% empty output
ind_pos = [];
t0_pos = [];
s0_pos = [];
% extract the negative slope crossing points
ind_neg = [];
t0_neg = [];
s0_neg = [];
end
end