Some of the most important concepts in electronics are signal and noise. A signal is what you came here for, and noise is everything else that is obscuring it. This is apparent if you are tuned into a radio station but are towards the edge of the station’s range; the static starts to make the broadcast inaudible.
To filter a measurement is to reduce the effect of noise and recover the signal. There is a broad range of filters to process data. One such filter which is on display here is known as a low pass filter. It is so named because it allows the low frequency components of the signal (the general upwards trend line) to “pass through”, while removing the high frequency components (the “jitters”). An excellent example of this is the monthly average temperature in a given location. On a daily basis, it is hard to discern a clear pattern, but when averaged over a month, the trend from one month to the next is much clearer.
Filters are absolutely necessary for us to be able to function in the real world, let alone one where our attention is saturated and dragged from one digital device to another. They are a vital means of simplifying the torrent of raw data we take in through all our senses.
Try this short meditation practice: choose an object around you and place a gentle focus on it, blocking out everything else around it. After two minutes, switch to be looking at the same object, but instead noticing everything except the object itself. What did you notice?
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