Filtering

Filtering can take place at analogue as well digital level.

These pages are mainly about

The content is mainly from a practical problem solving(signal filtering) view.

Two main topics in order:

1. analog filtering of signals before sampling aka anti aliasing filtering

2. Digital noise reduction after signal is sampled (digitized)

Analog filtering in inputs.

Analog filterering often takes at analog inputs where the analog signal will be digitalised by an ADC (Analog to Digital Converter). The purpose is to reduce the contents of high frequency components in the signal we must obey to the Nyquist-Shannon sampling theorem.

See more about analog low pass filtering and antialiasing here.

Digital filtering

After analog anti aliasing filters removal of high frequency noise in the digitized signal might be the next step.

The filtering is carried out on sampled data eg number values on integer or float format.

Two methods are presented here

• Simple Moving Average(SMA)

• Expotential Moving Average (EMA)

Thanks to https://tttapa.github.io/Pages/Mathematics/Systems-and-Control-Theory/Digital-filters/

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