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Re: gEDA-user: RMS Waveform of a signal
On 6/16/2010 10:43 AM, Rubén Gómez Antolí wrote:
Hello Armin:
Thanks for your response.
El 16/06/10 15:16, Armin Faltl escribió:
To the best of my knowledge, the RMS-value (root mean square) is a
constant,
i.e. the waveform would be a straight horizontal line. The definition of
the value comes from power considerations: it's the constant
current/voltage
that produces the same power(-dissipation) as the signal.
I'm not completly sure but, these are true when the signal is regular
and periodic.
I'm not sure what definition you have in mind for "regular".
If you have a "strange" wave, you get a time-variant rms wave. Look a
example on top of page 3 in this PDF:
http://fie-conference.org/fie96/papers/219.pdf
(plot RMS(i(r)))
Armin
Sincerily, I thought that this are more usual, but there are very few
references on web and nothing in how to obtain in "free world" (at
least, I can't find it).
RMS is usually not defined as time-varying. Usually you'd just find
sqrt(average_over_time(signal^2))
and for something which is not periodic (like say a digitally modulated
carrier with random data), you just average over enough time to where if
you did it again later you'd get about the same answer.
That RMS() function in the paper just uses a shorter window. In other
words what they do is compute:
sqrt(low_pass_filter(signal(t)*signal(t))
My guess is that the lowpass filter they use for the measurement is just
a moving average meaning the impulse response is a rectangular pulse
with a width of say 1/10 or so of the width of the waveform display.
So in octave you'd just square the signal, use the filter() function,
and then sqrt. The trick is something like octave usually doesn't work
on non-uniformly sampled data like what you'd get out of a simulator.
-Dan
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