I have some raw data that comes from a simulation. I take the sample points, and produce a moving average variable, and plot it against time. So imagine a signal that has peaks and valleys. The peaks represent periods of high activity, and the valleys represent periods of low activity.
What filter can I apply to this data to report the windows of high activity? We can assume that the windows do not overlap.
EDIT: The words "what filter can I apply" are not used correctly. I am not looking for a "filter". I am looking for a technique to find the windows. I start with the data, and all I want to do is find where the interesting windows of high activity are, so I can analyze them. You could say "just look at them", but I'm dealing with many data sets so that doesn't scale.