## 3 Results  
The presented modifications of the FDDA algorithm made it possible to reduce the calculation time by approximately eightfold (Table 2) and to make the results more plausible by reducing spatial distortions (Figure 7b) inherent to the original technique. In addition, the use of an activation function instead of a threshold algorithm improved the events' classification quality, showing that the shaker signal was more broadband and distributed in space than the PZT signal (Figure 7).  
Figure 6: SNR dependence on \(s_{t}\) and \(w_{\max}\). (**a**): SNR dependence when processing the frequency cross section (**c**); (**b**) SNR dependence when processing the spatial cross section (**d**).  
Data obtained using either the homemade or the commercial laser were processed with the presented implementation of MA-MD or AFDA, both individually and combined. The obtained results are presented in Figure 8. The corresponding SNR values for each case are presented in Table 1. This SNR was calculated for the data sets presented in Figure 8, as follows:  
\[\text{SNR}=10\log_{10}\left[\frac{s_{\text{max}}}{\left(\sum\limits_{j=1}^{k} \sum\limits_{i=1}^{n}s_{i,j}-s_{\text{max}}\right)/(k\cdot n-1)}\right] \tag{7}\]  
where \(s_{\text{max}}\) is the maximum useful signal level value in the data set; \(s_{i,j}\) is the \(i\), \(j\)th data set value, \(k\) is the data set size in spatial domain, and \(n\) is the data set size in the frequency domain.  
It can be seen that in all the studied cases, it was the combined use of the MA-MD and AFDA algorithms that led to the greatest increase in SNR. In addition, MA-MD is the most efficient when processing a signal with a frequency of 500 Hz, while AFDA is more efficient when processing a signal with the frequency of 8 kHz. Processing using any of the studied algorithms makes it possible to approximate the SNR of DAS data obtained using the homemade laser to the SNR of data obtained using the commercial laser. For the homemade laser, the most optimal MA and MD windows values for each of the useful signal frequencies turned out to be slightly different from those for the commercial laser. Thus, for the homemade laser and 500 Hz event, the MA and MD window sizes were 14 counts and 20 counts, respectively, or 19 counts and 15 counts. For the 8 kHz event, these values were 1 and 1, respectively. Just as in the first case, matrix symmetry was observed, similar to Figure 3a, as well as interchangeability of the window sizes with a small error. In the second case, the optimal window sizes turned out to be completely interchangeable and equal. This was probably caused by a slight impact frequency shift, which is actually present in the data and has already been stated by our team [33].  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Algorithm** & **Computation Time, s** & **Spatial Resolution, m** \\ \hline MA-MD & 13.1 & 1 \\ \hline AFDA & 24.9 & 1 \\ \hline FDDA & 200.0 & 100 \\ \hline \hline \end{tabular}
\end{table}
Table 2: Algorithms’ computation time comparison.  
Figure 7: (**a**) Original data set; (**b**) data processed by the FDDA algorithm, with red arrows indicating excessive spatial distortions; (**c**) data processed by the AFDA algorithm.