I thought of trying something like this, but there are bound to be some compromises, aren't there? I mean, just from the inherent compromises of FFT. Unless, I suppose, you added the new imaginary part to the original untouched real part. And when you say "continuous"... I guess you don't really mean "continuous" as in "not discrete"...?

[czero~] is just that, y[n] = x[n] - a[n] * x[n-1], which I take to mean: Y[n] = X[n] - A[n] * X[n-1]

And so I'm thinking the real and imaginary parts of A[n] could be anything at all, but I want to try and see.

-Chuckk

On 6/10/06, Charles Henry czhenry@gmail.com wrote:

Hi, Chuck The Hilbert transform does create a continuous complex signal from a real-valued signal, Y. You take the Hilbert transform as 2*IFFT( X ) where X is the FFT of Y with the second half of X replaced by zeros.

This creates what is called the analytic signal, which has an identical real part to the signal we started with, and an imaginary signal that matches the real part. There is exactly one imaginary signal to correspond to a real signal.

You may find something in the examples about a Hilbert transform (but I don't trust it). It would be pretty simple to just write another external for it (using the mayer fft).

What's czero~ ? Is that a filter with a zero, some place in the complex (Laplace) domain?

Chuck

On 6/10/06, Chuckk Hubbard badmuthahubbard@gmail.com wrote:

...

I'm teaching myself some DSP stuff, using Miller's Techniques, a Digital Filters book, and some other references, and I'm loving it. I am wondering, though, how one comes up with a complex audio signal for use in Pd. I want to experiment with [czero~], and I've also wondered where complex signals come from for [fft~]. It doesn't seem like it would be possible to create a complex signal from a real one, but maybe there are ways to synthesize them?

Thanks. -Chuckk

-- "Far and away the best prize that life has to offer is the chance to work hard at work worth doing." -Theodore Roosevelt

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