It is frequently necessary to establish similarity between one set of data and another. It means we would like to correlate two processes or data. Correlation is closely related to convolution, because the correlation is essentially convolution of two data sequences in which one of the sequences has been reversed.

Applications are in

1) Images processing for robotic vision or remote sensing by satellite in which data from different image is compared

2) In radar and sonar systems for range and position finding in which transmitted and reflected waveforms are compared.

3) Correlation is also used in detection and identifying of signals in noise.

4) Computation of average power in waveforms.

5) Identification of binary codeword in pulse code modulation system.

Difference Between Linear Convolution And Correlation

Types Of Correlation

Under Correlation there are two classes.

1) CROSS CORRELATION: When the correlation of two different sequences x(n) and y(n) is performed it is called as Cross correlation. Cross-correlation of x(n) and y(n) is rxy(l) which can be mathematically expressed as

2) AUTO CORRELATION: In Auto-correlation we correlate signal x(n) with itself, which can be mathematically expressed as

Properties Of Correlation