Cross-correlation

Proving the upper bound of cross correlation

Proving the upper bound of cross correlation
  1. How do you test cross-correlation?
  2. What does high cross-correlation mean?
  3. What does cross-correlation tell you?

How do you test cross-correlation?

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 high cross-correlation mean?

Cross-correlation is generally used when measuring information between two different time series. The possible range for the correlation coefficient of the time series data is from -1.0 to +1.0. The closer the cross-correlation value is to 1, the more closely the sets are identical.

What does cross-correlation tell you?

In signal processing, cross-correlation is a measure of similarity of two series as a function of the displacement of one relative to the other. This is also known as a sliding dot product or sliding inner-product. It is commonly used for searching a long signal for a shorter, known feature.

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