So I have this signal that tends to vary in both mean and overall shape, and I believe there is a transient part in the signal that I would like to extract somehow. Given the appearance of the signal I’m not sure which method is reliable. I have tried computing the variance using the movvar function and find that the variance drops after a few seconds. So my question is: is there any good way of identifying transient parts of a more complicated signal? Here is an example of how my signal looks like.So I have this signal that tends to vary in both mean and overall shape, and I believe there is a transient part in the signal that I would like to extract somehow. Given the appearance of the signal I’m not sure which method is reliable. I have tried computing the variance using the movvar function and find that the variance drops after a few seconds. So my question is: is there any good way of identifying transient parts of a more complicated signal? Here is an example of how my signal looks like. So I have this signal that tends to vary in both mean and overall shape, and I believe there is a transient part in the signal that I would like to extract somehow. Given the appearance of the signal I’m not sure which method is reliable. I have tried computing the variance using the movvar function and find that the variance drops after a few seconds. So my question is: is there any good way of identifying transient parts of a more complicated signal? Here is an example of how my signal looks like. time series, matlab MATLAB Answers — New Questions

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