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Using FFT to analyse and cleanse Time Series Data

Digitalize Product and unexpected noise

The challenge

Often when dealing with IOT data, the biggest challenge is encountering unexpected noise. This noise can be very troublesome when you want to derive values from the signal. The noise can easily mislead your models with inaccurate values The challenge lies in how we can clean the noise from the data when (often) we don’t know the frequency of which. To make matters worse, these frequencies may varying constantly due to the operating conditions of sensors. A possible solution is to decompose the signal. Once decomposed, it will be easier to filter out the nose.

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Using FFT to analyse and cleanse time series data.pdf