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Comedi

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• TRIG_ROUND_NEAREST: round to nearest supported timing period, the default. This ﬂag (as well as the following three),

indicates how timing arguments should be rounded if the hardware cannot achieve the exact timing requested.

• TRIG_ROUND_DOWN: round period down.

• TRIG_ROUND_UP: round period up.

• TRIG_ROUND_UP_NEXT: this one doesn’t do anything, and I don’t know what it was intended to do. . . ?

• TRIG_DITHER: enable dithering? Dithering is a software technique to smooth the inﬂuence of discretization ‘noise’.

• TRIG_DEGLITCH: enable deglitching? Another ‘noise’ smoothing technique.

• TRIG_WRITE: write to bidirectional devices. Could be useful, in principle, if someone wrote a driver that supported com-

mands for a digital I/O device that could do either input or output.

• TRIG_BOGUS: do the motions?

• TRIG_CONFIG: perform conﬁguration, not triggering. This is a legacy of the deprecated comedi_trig_struct data structure,

and has no function at present.

4.5.5 Anti-aliasing

If you wish to aquire accurate waveforms, it is vital that you use an anti-alias ﬁlter. An anti-alias ﬁlter is a low-pass ﬁlter used

to remove all frequencies higher than the Nyquist frequency (half your sampling rate) from your analog input signal before you

convert it to digital. If you fail to ﬁlter your input signal, any high frequency components in the original analog signal will create

artifacts in your recorded digital waveform that cannot be corrected.

For example, suppose you are sampling an analog input channel at a rate of 1000 Hz. If you were to apply a 900 Hz sine wave to

the input, you would ﬁnd that your sampling rate is not high enough to faithfully record the 900 Hz input, since it is above your

Nyquist frequency of 500 Hz. Instead, what you will see in your recorded digital waveform is a 100 Hz sine wave! If you don’t

use an anti-alias ﬁlter, it is impossible to tell whether the 100 Hz sine wave you see in your digital signal was really produced by

a 100 Hz input signal, or a 900 Hz signal aliased to 100 Hz, or a 1100 Hz signal, etc.

In practice, the cutoff frequency for the anti-alias ﬁlter is usually set 10% to 20% below the Nyquist frequency due to fact that

real ﬁlters do not have inﬁnitely sharp cutoffs.

4.6 Slowly-varying inputs

Note: The functions described here use an old feature that is no longer implemented by the Comedi kernel layer. THEY

WILL NOT WORK!

Sometimes, your input channels change slowly enough that you are able to average many successive input values to get a more

accurate measurement of the actual value. In general, the more samples you average, the better your estimate gets, roughly by a

factor of sqrt(number_of_samples). Obviously, there are limitations to this:

• you are ultimately limited by ‘Spurious Free Dynamic Range’. This SFDR is one of the popular measures to quantify how

much noise a signal carries. If you take a Fourier transform of your signal, you will see several ‘peaks’ in the transform: one

or more of the fundamental harmonics of the measured signal, and lots of little ‘peaks’ (called ‘spurs’) caused by noise. The

SFDR is then the difference between the amplitude of the fundamental harmonic and of the largest spur (at frequencies below

half of the Nyquist frequency of the DAQ sampler!).

• you need to have some noise on the input channel, otherwise you will be averaging the same number N times. (Of course, this

only holds if the noise is large enough to cause at least a one-bit discretization.)

• the more noise you have, the greater your SFDR, but it takes many more samples to compensate for the increased noise.

• if you feel the need to average samples for, for example, two seconds, your signal will need to be very slowly-varying, i.e., not

varying more than your target uncertainty for the entire two seconds.

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