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  2. Template:Correlation and covariance - Wikipedia

    en.wikipedia.org/wiki/Template:Correlation_and...

    Template: Correlation and covariance. ... Autocorrelation matrix; Cross-correlation matrix; Auto-covariance matrix; Cross-covariance matrix; For stochastic processes.

  3. Multivariate random variable - Wikipedia

    en.wikipedia.org/wiki/Multivariate_random_variable

    The correlation matrix (also called second moment) of an random vector is an matrix whose (i,j) th element is the correlation between the i th and the j th random variables.

  4. Covariance and correlation - Wikipedia

    en.wikipedia.org/wiki/Covariance_and_correlation

    With any number of random variables in excess of 1, the variables can be stacked into a random vector whose i th element is the i th random variable. Then the variances and covariances can be placed in a covariance matrix, in which the (i, j) element is the covariance between the i th random variable and the j th one.

  5. Spatial correlation (wireless) - Wikipedia

    en.wikipedia.org/wiki/Spatial_correlation_(wireless)

    Spatial correlation means that there is a correlation between the received average signal gain and the angle of arrival of a signal. Rich multipath propagation decreases the spatial correlation by spreading the signal such that multipath components are received from many different spatial directions. [ 1 ]

  6. Cross-correlation - Wikipedia

    en.wikipedia.org/wiki/Cross-correlation

    [12] [13] [clarification needed] After calculating the cross-correlation between the two signals, the maximum (or minimum if the signals are negatively correlated) of the cross-correlation function indicates the point in time where the signals are best aligned; i.e., the time delay between the two signals is determined by the argument of the ...

  7. Matched filter - Wikipedia

    en.wikipedia.org/wiki/Matched_filter

    In signal processing, the output of the matched filter is given by correlating a known delayed signal, or template, with an unknown signal to detect the presence of the template in the unknown signal. [1] [2] This is equivalent to convolving the unknown signal with a conjugated time-reversed version of the template.