how to count no. of elements exceeding given threshold value in selected moving window

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Jay Hanuman
Jay Hanuman 2016-10-27
编辑： Jay Hanuman 2016-10-27
I have time vs values plot. time length=100, I want count number of values exceeds 20 for time window 4, then skipping 1st & adding next time so window size should be constant 4, and count number of values which exceeds 20.

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回答（3 个）

Image Analyst
Image Analyst 2016-10-27
Try movsum(). (It's a fairly new function).
% Create 30 random values.
signal = randi(100, 1, 30)
% Only want values more than 20 in the sum so set those under to 0
signal(signal <= 20) = 0
% Compute the moving sum
summedSignal = movsum(signal, 4)
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Image Analyst
Image Analyst 2016-10-27
Nothing in my code (other than generating some sample data) has any reliance on the length of the signal being 40 or 100 or anything else. Any length signal will work. If it's longer and you only want the first 40, then crop it off
theSum = theSum(1:40); % Take only the first 40.
Jay Hanuman
Jay Hanuman 2016-10-27
编辑：Jay Hanuman 2016-10-27
for next 41 to 100 I have to do same operation but with value comes below 20 (but not exceed 20) & for different window size so I am thinking there is way to do above for only 40

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Steven Lord
Steven Lord 2016-10-27
It's not really clear to me from your description whether the window length is fixed (in which case I recommend using the movsum function that was introduced in release R2016a) or whether the window length can vary and the endpoints of the window are selected based on the sum of the elements in the window.
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Jay Hanuman
Jay Hanuman 2016-10-27
time length =100, so 1st 1 to 4, then 2 to 5 likewise, at last 97 to 100 then stop. and I want number of elements which are exceeding limit, not sum of values i.e. in particular window, 4 values are 12 34 36 25 so ans would be 3.

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Walter Roberson
Walter Roberson 2016-10-27
above_threshold = (values(:) > 20) .';
cum_above = cumsum([0 above_threshold]);
running_count = cum_above(5:end) - cum_above(1:end-4);
or
above_threshold = (values(:) > 20) .';
running_count = conv(above_threshold, ones(1,4), 'valid');
Note that these will be shorter than the original time series because they only use full windows.

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