Soft dB Zen-Ten User guide - Manual (Page 28)

User manual for the ZEN 3-channel X-LMS controller Soft dB inc.
2) Identification of control output #2 and reference #2: filter C2R2
3) Identification of control output #3 and reference #3: filter C3R3
The Secondary path identification function does the following identifications:
Case coupled:
1) Identification of control output #1 and error #1: filter: C1E1
2) Identification of control output #2 and error #1: filter: C2E1
3) Identification of control output #3 and error #1: filter: C3E1
4) Identification of control output #1 and error #2: filter: C1E2
5) Identification of control output #2 and error #2: filter: C2E2
6) Identification of control output #3 and error #2: filter: C3E2
7) Identification of control output #1 and error #3: filter: C1E3
8) Identification of control output #2 and error #3: filter: C2E3
9) Identification of control output #3 and error #3: filter: C3E3
Case uncoupled:
1) Identification of control output #1 and error #1: filter C1E1
2) Identification of control output #2 and error #2: filter C2E2
3) Identification of control output #3 and error #3: filter C3E3
After launching the identification process, white noise is generated by the control source,
and the DSP’s LMS algorithm optimizes the control path FIR model. Theoretically, and
if the background noise is low and Mu=1 is used, convergence is very fast (about 10
seconds) and the user can confirm the end of the identification process with the control
Ok. A convergence of –25 dB is really good and adequate for all control path models.
However, if the primary source to control is operational or if the background noise level
is high, we suggest using the identification technique for noisy conditions described in
the section 3.3.2.
During the identification process, white noise volume can be adjusted so as to improve
convergence. However, if the white noise volume is too high, the control source can
become non-linear and the precision of the model (and the convergence) will decrease.
On the other hand, if the white noise volume is too low, the signal on noise ratio is low
and the identification is not precise. To increase precision, we suggest keeping the white
noise volume at 50% if possible, and using an external volume (or the onboard output
attenuator) to adjust the dynamic. In this way, the computation dynamic on the DSP will
be optimized.
To verify the dynamics of all signals used during the identification process, the user can
start an acquisition by using the Start control. Signal selection is done using the Show
Signal control. Acquisition can be done in continuous mode (Expo) or for a fixed number
of blocks (Lin mode). The graph in the lower part of the interface shows the time signal
or the average power spectrum (selection is done via the Freq/Time control).
ZEN User Manual p. 28