Autocorrelation analysis

Consists of correlating the data at a particular time with data at an earlier time. Accommodates searches for the existence of repeatable cycles. If data are suspected of containing a repeating cycle, autocorrelation analysis can help to determine if such a cycle is really there. Autocorrelation is a mathematical tool used frequently in signal processing for analyzing functions or series of values, such as time domain signals. It is the cross-correlation of a signal with itself. Autocorrelation is useful for finding repeating patterns in a signal, such as determining the presence of a periodic signal which has been buried under noise, or identifying the fundamental frequency of a signal which doesn't actually contain that frequency component, but implies it with many harmonic frequencies.