Howtosignalprocessing
- What is meant by cross-correlation?
- What is the formula for cross-correlation?
- What are the properties of cross-correlation?
- What is the difference between convolution and cross-correlation?
What is meant by cross-correlation?
Cross-correlation is used to evaluate the similarity between the spectra of two different systems, for example, a sample spectrum and a reference spectrum. This technique can be used for samples where background fluctuations exceed the spectral differences caused by changes in composition.
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 ) ] .
What are the properties of cross-correlation?
The cross correlation function between two different signals is defined as the measure of similarity or coherence between one signal and the time delayed version of another signal. The cross correlation function is defined separately for energy (or aperiodic) signals and power or periodic signals.
What is the difference between convolution and cross-correlation?
In signal / image processing, convolution is defined as it is defined as the integral of the product of the two functions after one is reversed and shifted. On the other hand, cross-correlation is known as sliding dot product or sliding inner-product of two functions. The filter in cross-correlation is not reversed.
