I have a pulse signal from which I sample N times of level changes (e.g. high->low).
At undefined times the pulses in the original signal are completely missing. This leads to wrong number of measured original samples (N+m, m: count of lost samples).
I have implemented a naive detection algorithm:
prev_time = x[n-1] - x[n-2] act_time = x[n] - x[n-1] if (act_time / prev_time > 1.7) missing_sample_detected()
My questions are:
- Is this the way to go?
- What alternative algorithms exists for detecting the position of missing samples?
- Can you suggest some literature on this topic? Atm i'm looking at "nonuniform sampling" but not sure if it's the right place to look for this problem