periodicity

Terms from Artificial Intelligence: humans at the heart of algorithms

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Periodicty refers to time-series, sequential data that has behvaiours that recur at fixed periods. For example, in the UK summer temeratures tend to be warmer than winter temperatures. As is evident from the weather example, this does not mean precisely repeating itself. In stochastic processes or those where there are additional effects, there is rarely an exact repetition, however the period over which the phenoman acts is fixed, for example daily or annually. This means there are long-term correlations between the data at multiples of the period.

In contrast, quasi-periodic processes have an approxiamte period of behaviior, but this can drift over time, so that there is no very long-term correltion at multiples of the period.

Used in Chap. 14: page 222