I am working on a temperature
time-series data which is very noisy. I am trying to measure true low
and high
temperature but because of noise, I can not apply peak detection
directly. I need to do some filtering. Since sampling frequency Fs
is not known for this data, I have applied two types of filter
- Kalman filter
orange
lines are the original signal and blue
lines are filtered signal. The median filter seems good in this example which is preserving edges.
I want to know what are other types of filters which I can apply to get rid of noise without affecting the sharp edges of the signal.