Plot y[n]

Fig. 21 shows a typical view of the y[n] tab for plotting the transient response and its Fourier transformation, here, for a Chebychev filter (IIR).

Screenshot of the y[n] tab (time domain)

Fig. 21 Screenshot of the y[n] tab (time domain)

This tab is split into several subwindows:

Time / Frequency (main plotting area)

These vertical tabs select between the time (transient) and frequency (spectral) domain. Signals are calculated in the time domain and then transformed using Fourier transform.

Time

Frequency

The Fourier transform of the transient signal can be viewed in the vertical tab “Frequency” (Fig. 22). This is especially important for fixpoint simulations where the frequency response cannot be calculated analytically.

Screenshot of the h[n] tab (frequency domain)

Fig. 22 Screenshot of the y[n] tab (frequency domain)

For an transform of periodic signals without leakage effect, (“smeared” spectral lines) take care that:

  • The filter has settled sufficiently. Select a suitable value of N0.

  • Choose the number of data points N in such a way that an integer number of periods is displayed (and transformed).

  • The FFT window is set to rectangular. Other windows work as well but they distribute spectral lines over several bins. When it is not possible to capture an integer number of periods, use another window as the rectangular window has the worst leakage effect.

Plots

What will be plotted and how.

Stim.

Select the stimulus, its frequency, DC-content, noise … When the BL checkbox is checked, the signal is bandlimited to the Nyquist frequency. Some signals have strong harmonic content which produces aliasing. This can be seen best in the frequency domain (e.g. for a sawtooth signal with f = 0.15).

DC and Different sorts of noise can be added.

Run

Usually, plots are updated as soon as an option has been changed. This can be disabled with the Auto checkbox for cases where the simulation takes a long time (e.g. for some fixpoint simulations).

Development

More info on this widget can be found under plot_impz.