Alright.... here is my last version of the patches. Even if no one else is interested, I consider the problem solved at this point. Whenever the calculations are reset, there is a brief transient. digression: That's because I can't find a way to precisely calculate a signal which represents the sum of squares of s1, as follows: output(k)=sum(i= -32+k:31+k; s1(i)^2) for k=-32:31 in the same block as sxcov~ (I tried to do that first, but no easy solution came up, so I chose something simpler, if only a little less accurate)

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anyway, each of the patches from previous posts have been modified and corrected. Hopefully, this method gives you the most flexibility for computing sxcov~ and sxcorr~ in real time with abstractions. Chuck On 6/20/07, Charles Henry <[EMAIL PROTECTED]> wrote:

> This one works within block sizes of 64, by using an [block~ 128 2] . Now, I've got one where you add an argument and use arbitrary block sizes. It's much more useful, this way. [sxcov~ 2048] works within a blocksize of 2048, and calculates the symmetric cross covariance of two signals. Still having aggravating time, trying to normalize by the proper calculation of variance on each signal. It might be a while before I get it together. Chuck

**
sxcov~.pd**

*Description:* Binary data

**
sxcov~-test.pd**

*Description:* Binary data

**
sxcorr~.pd**

*Description:* Binary data

**
sxcorr~-test.pd**

*Description:* Binary data

**
conj_mult~.pd**

*Description:* Binary data

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