Howtosignalprocessing
- What is autocorrelation of two signals?
- How do you calculate autocorrelation of a signal?
- How do you cross correlate two signals?
- What does ACF measure?
What is autocorrelation of two signals?
Autocorrelation, sometimes known as serial correlation in the discrete time case, is the correlation of a signal with a delayed copy of itself as a function of delay. Informally, it is the similarity between observations of a random variable as a function of the time lag between them.
How do you calculate autocorrelation of a signal?
The number of autocorrelations calculated is equal to the effective length of the time series divided by 2, where the effective length of a time series is the number of data points in the series without the pre-data gaps. The number of autocorrelations calculated ranges between a minimum of 2 and a maximum of 400.
How do you cross correlate two signals?
To detect a level of correlation between two signals we use cross-correlation. It is calculated simply by multiplying and summing two-time series together. In the following example, graphs A and B are cross-correlated but graph C is not correlated to either.
What does ACF measure?
The autocorrelation function (ACF) defines how data points in a time series are related, on average, to the preceding data points (Box, Jenkins, & Reinsel, 1994). In other words, it measures the self-similarity of the signal over different delay times.
