Howtosignalprocessing
- How do you interpret cross-correlation?
- How do you read a CCF plot?
- What is cross-correlation example?
- What is the formula for cross-correlation?
How do you interpret cross-correlation?
Understanding Cross-Correlation
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.
How do you read a CCF plot?
A plot of the X data vs. the Y data at lag 𝑘 may show a positive or negative trend. If the slope is positive, the cross correlation is positive; if there is a negative slope, the cross correlation is negative.
What is cross-correlation example?
Cross-correlation is the comparison of two different time series to detect if there is a correlation between metrics with the same maximum and minimum values. For example: “Are two audio signals in phase?” Normalized cross-correlation is also the comparison of two time series, but using a different scoring result.
What is the formula for cross-correlation?
Cross-correlation between Xi and Xj is defined by the ratio of covariance to root-mean variance, ρ i , j = γ i , j σ i 2 σ j 2 . γ ^ i , j = 1 N ∑ t = 1 N [ ( X i t − X ¯ i ) ( X j t − X ¯ j ) ] .
