Finding a maximum signal variation in MATLAB

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Jimmy
Jimmy el 5 de Ag. de 2015
Comentada: Image Analyst el 22 de Mayo de 2016
I have a signal which consist of one 1000000x1 array (data) and one 1000000x1 array (time). I'm having problem to detect the location where the signal have the largest variation with respect to the value of the array.
For example in this signal, I want to locate the variation of the signal from time 4 until 11. I found out that findpeaks command will detect all peaks but I want to detect only the highest peak(highest value from the array) and the data (eg: 5000 sampling) to the right and left from the highest peak.
Thank you in advance.

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Star Strider
Star Strider el 5 de Ag. de 2015
If you are only finding one peak each time, I would use the max and min functions, each with two outputs, to get the absolute maximum and minimum. The second output is the index location of the maximum or minimum.
You can also use the Signal Processing Toolbox findpeaks function on the original signal to get the value and location of the highest peak, the use findpeaks again on the negative of the original signal to get that highest value and location.
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Star Strider
Star Strider el 22 de Mayo de 2016
I do not have enough recent experience with wavelets to provide the guidance you need.
It would be best if you post this as a new Question.
Jimmy
Jimmy el 22 de Mayo de 2016
I see. Ok noted. Thank you for the tutorial and guidance that you have been given since I posted this question. It was a great help.

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Más respuestas (2)

Image Analyst
Image Analyst el 5 de Ag. de 2015
Editada: Image Analyst el 5 de Ag. de 2015
Just threshold and call bwareaopen(). See my answer here: http://www.mathworks.com/matlabcentral/answers/231181#answer_187244
  5 comentarios
Jimmy
Jimmy el 6 de Ag. de 2015
The attached file contains the 1000000x1 data array and 1000000x1 time array.
Figure below shows the output of the signal from the coding: plot(time,data)
I want to extract the signal only from area 1 to 2
Thank you
Jimmy
Jimmy el 6 de Ag. de 2015
This is the attached file.
Thank you

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Greg Dionne
Greg Dionne el 24 de Ag. de 2015
You could also try envelope:
envelope(data-mean(data),20000,'rms')
rmsEnv = envelope(data-mean(data),20000,'rms');
envTime = time(rmsEnv>0.02);
envData = data(rmsEnv>0.02);
plot(envTime, envData)
  3 comentarios
Star Strider
Star Strider el 24 de Ag. de 2015
It’s a FEX contribution. There appear to be several like it.
Image Analyst
Image Analyst el 22 de Mayo de 2016
envelope() is now in the Signal Processing Toolbox. I haven't played around with it yet so I don't have a demo on this function.

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