Cross-correlation

Cross correlation example

Cross correlation example
  1. What is cross-correlation example?
  2. Where is cross-correlation used?
  3. What is the formula for cross-correlation?
  4. How does cross-correlation work?
  5. What is cross-correlation of two signals?
  6. Is cross-correlation same as Pearson correlation?

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.

Where is cross-correlation used?

Cross-correlation is used in portfolio management to measure the degree of diversification among the assets contained in a portfolio. Modern portfolio theory (MPT) uses a measure of the correlation of all the assets in a portfolio to help determine the most efficient frontier.

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 ) ] .

How does cross-correlation work?

Cross correlation happens when two different sequences are correlated. Autocorrelation is the correlation between two of the same sequences. In other words, you correlate a signal with itself.

What is cross-correlation of two signals?

Correlation of two signals is the convolution between one signal with the functional inverse version of the other signal. The resultant signal is called the cross-correlation of the two input signals. The amplitude of cross-correlation signal is a measure of how much the received signal resembles the target signal.

Is cross-correlation same as Pearson correlation?

The Pearson product-moment correlation coefficient is simply a normalized version of a cross-correlation. When two times series data sets are cross-correlated, a measure of temporal similarity is achieved. The cross-correlation function in its simplest form is easy to use and quiet intuitive.

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