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.
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)

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.


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.


Attachment: sxcov~.pd
Description: Binary data

Attachment: sxcov~-test.pd
Description: Binary data

Attachment: sxcorr~.pd
Description: Binary data

Attachment: sxcorr~-test.pd
Description: Binary data

Attachment: conj_mult~.pd
Description: Binary data

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