Difference between cross correlation definitions (signal processing / random processes)

1. What is the difference between auto correlation and cross-correlation of signals?
2. What is cross-correlation in random process?
3. What is the difference between cross-correlation and convolution?
4. What is the relation between cross-correlation and autocorrelation?

What is the difference between auto correlation and cross-correlation of signals?

Crosscorrelation is a measure of similarity between two signals, while autocorrelation is a measure of how similar a signal is to itself. Autocorrelation for stochastic signals and the crosscorrelation between input and output signals to help identify an unknown system have been discussed earlier.

What is cross-correlation in random process?

The cross-correlation between random processes X(t) and Y(t) is a measure of the correlation between them at two different time points. The power spectral density (PSD) is defined as the amount of power in each frequency band and is the Fourier transform of the autocorrelation function.

What is the difference between cross-correlation and convolution?

Cross-correlation and convolution are both operations applied to images. Cross-correlation means sliding a kernel (filter) across an image. Convolution means sliding a flipped kernel across an image.

What is the relation between cross-correlation and autocorrelation?

Normalized auto-correlation is the same as normalized cross-correlation, but for auto-correlation, thus comparing one metric with itself at a different time. Time Shift can be applied to all of the above algorithms. The idea is to compare a metric to another one with various “shifts in time”.