Autocorrelation value is 0.3 and input cross-correlation error value is 3.Are the obtained results after training ANN is correct or wrong?
In signal processing, cross-correlation is a measure of similarity of two series as a function of the displacement of one relative to the other. This is also known as a sliding dot product or sliding inner-product. 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. The cross-correlation is similar in nature to the convolution of two functions. In an autocorrelation, which is the cross-correlation of a signal with itself, there will always be a peak at a lag of zero, and its size will be the signal energy.
Prashant Kumar ,
As shared by Rachit, it is true that the autocorrelation is convolution of the signal with itself and is generally expected to be a large value at a lag of zero (due to obvious reasons). And cross correlation is supposed to have a minimum value.
ACF and PACF tests can be used in MATLAB to find their values at variable lags.
Your question is not so clear. Where exactly do you want to find an application in terms of input cross correlation error?
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