Signal processing toolbox provides functions that let you compute correlation, convolution, and transforms of signals. Correlation dimension is the measure of dimensionality of the space occupied by a set of random points. Signal processing toolbox provides a family of correlation and convolution functions that let you detect signal similarities. Choose a web site to get translated content where available and see local events and offers. It uses the normalized cross correlation matrix function normxcorr2. Cross correlation measures the similarity between a vector x and shifted lagged copies of a vector y as a function of the lag. For example, you can specify whether to use pearson or spearman partial correlations, or specify how to treat missing values. Determine periodicity, find a signal of interest hidden in a long data record, and measure delays between signals to synchronize them. If x and y have different lengths, the function appends zeros to the end of the shorter vector so it has the same length as the other. The values of the coefficients can range from 1 to 1, with 1 representing a direct, negative correlation, 0 representing no correlation, and 1 representing a direct, positive correlation. Crosscorrelation matlab xcorr mathworks united kingdom.
In this case i would use the following code in matlab, based on. This is brief introduction to template matching in matlab. Visualization of cross correlation and convolution with matlab reza arfa. Use the fast fourier transform to decompose your data into frequency components.
122 239 587 719 1496 325 670 927 1046 566 1150 1473 265 276 1051 542 1334 1493 1500 427 1179 945 1581 499 236 659 1459 930 376 1514 458 568 1082 911 438 926 1044 913 480 1194 126 198 63 365 283 632