Cross-correlation

In signal processing, cross-correlation is a measure of similarity of two series as a function of the lag of one relative to the other. This is also known as a sliding dot product or sliding inner-product.

Description

It is commonly used for searching a long signal for a shorter, known feature.

It has applications in pattern recognition, single particle analysis, electron tomography, averaging, cryptanalysis, and neurophysiology.

See also

• Autocorrelation
• Autocovariance
• Coherence
• Convolution - a mathematical operation on two functions (f and g).
• Correlation
• Correlation function
• Cross-covariance
• Cross-spectrum
• Covariance mapping
• Digital image correlation
• Phase correlation
• Scaled correlation
• Signal processing
• Spectral density
• Wiener–Khinchin theorem

External links

• Cross-correlation @ Wikipedia