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Circular discontinuity

Sometimes the variables we present to neural networks are fundamentally circular.

Examples are a rotating piece of machinery, or the dates in the calendar year.

These variables introduce a special problem due to the fact that they have a discontinuity, i.e. we have a serious problem as the object passes from 360 degrees to 0 degrees or from 31st December to 1st January (i.e. day 365 to day 1).

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