# Adjustable Structure for Feedback Active Headest System Using the Virtual Microphone Method
## 5 Real-Time Experimental Results and Discussion
### Experiment 3: Varying Primary Sources  
In some cases, the primary sources are usually uncertain [6]. With the dummy head and proposed structure in the nominal position, four different primary disturbance configurations were investigated, as shown in Table 2. As a benchmark for the optimal possible performance with this setup, the signals obtained from the target microphones at the ears of the dummy head were applied as error signals for direct control. The secondary paths, additional filters, and observation filters that need to be pre-modeled were measured for the first disturbance configuration only and applied generically to all other configurations.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Disturbance Configuration** & **Direct Control** & **AFM** & **RMM** & **VMM** \\ \hline Noise 1, Position 1 & 26.90/26.23 & 24.45/23.33 & 24.20/23.06 & 19.29/19.46 \\ Noise 2, Position 1 & 25.33/25.18 & 3.64/4.67 & 12.92/13.49 & 19.50/19.32 \\ Noise 1, Position 2 & 26.59/25.31 & 7.86/8.68 & 2.88/3.11 & 19.03/19.79 \\ Noise 1, Position 1 \& 2 & 27.72/26.69 & 11.07/11.40 & 8.46/9.20 & 18.75/18.59 \\ \hline \hline \end{tabular}
\end{table}
Table 2: Comparison between the reduction (dB) attained by various methods with four disturbance configurations at the left and right ears of the dummy head.  
Figure 7: Noise attenuation (dB) at the ears as the dummy head moved in the \(x\) direction when employing various headrest structures and VS methods. (**a**) AFM, left ear. (**b**) RMM, left ear. (**c**) VMM, left ear. (**d**) AFM, right ear. (**e**) RMM, right ear. (**f**) VMM, right ear.  
Figure 8 illustrates the amplitude spectrum with and without cancellation at the left ear in the case of various algorithms and different disturbance configurations. According to the results shown in Table 2 and Figure 8, the maximum attenuation performance for all the configurations was achieved when the target microphones were directly controlled. It was hardly affected by any changes to the primary source. The performance of the RMM was mainly influenced by varying the positions of the primary source. In contrast, the efficiency of AFM was more susceptible to varying disturbance signal characteristics and less sensitive to changes in the primary source positions. As the quantity of the primary source increased, the performance of the AFM and RMM fell between the attenuation for configurations 1 and 3 while the AFM produced a better performance. Compared to the AFM and RMM, the VMM was less affected by changes in primary sources. This was attributed to the fact that, when the configuration of the primary noise was switched, the pre-trained additional observation filters was inappropriate and the effectiveness of the AFM/RMM deteriorated drastically, as a result [19]. The VMM eliminates the requirement for these additional transfer functions but, therefore, had the worst performance in the nominal condition (configuration 1).  
Based on all the above experiments with the proposed adjustable headrest structure applied, when the primary source was stable, it was confirmed that the AFM and RMM had similar performance, and they outperformed the VMM. When the primary source changed and it was not feasible to re-measure any transfer function in some cases, the effectiveness of the AFM and RMM decreased while the VMM provided the most stable performance as a trade-off. Therefore, it was important to choose the appropriate VS methods based on the details of the application instead of just the nominal performance.  
Figure 8: Amplitude spectrum at the left ear of the dummy head under various algorithms and disturbance configurations. (**a**) First disturbance configuration. (**b**) Second disturbance configuration. (**c**) Third disturbance configuration. (**d**) Fourth disturbance configuration.