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R = covf(data,M) R = covf(data,M,maxsize)
data is an iddata object and M is the maximum delay -1 for which the covariance function is estimated. The routine is intended for time-domain data only.
Let z contain the output and input channels
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where y and u are the rows of data.OutputData and data.InputData, respectively, with a total of nz channels.
R is returned as an nz2 -by- M matrix with entries
![]()
where
is the jth row
of z, and missing values in the sum are replaced
by zero.
The optional argument maxsize controls the memory size as explained under Algorithm Properties.
The easiest way to describe and unpack the result is to use
reshape(R(:,k+1),nz,nz) = E z(t)*z'(t+k)
Here ' is complex conjugate transpose, which also explains how complex data is handled. The expectation symbol E corresponds to the sample means.
When nz is at most two, and when permitted by maxsize, a fast Fourier transform technique is applied. Otherwise, straightforward summing is used.
| iddata | |
| spa |
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