# Dimension Reduction Using New Bond Graph Algorithm and Deep Learning Pooling on EEG Signals for BCI
## 4 Experiment and Results
### Experiments and Scenarios
#### 4.4.2 Results of Second Model Scenario  
In the following, we will examine the results of the hybrid signals, i.e., a combination of filter banks (a) 2 and 5 presented in Table 9, (b) 2, 5, and 6 presented in Table 10, and (c) 2, 5, 6, and 9 presented in Table 11. Such cases do not exist in nature for recording, and no system can record such models. Hence, we generate them offline. We have highlighted the highest obtained accuracies in these tables, similar to the previous two tables presented above. For these cases, our proposed algorithm mostly had the highest accuracies for channel 12. In addition, our algorithm demonstrated higher average accuracies in all of the cases. In Table 11, similar to Table 9, in channel 12, the majority of the best accuracies was obtained by our algorithm. According to the results presented in Tables 7-11, in general, the algorithms perform better in channel 12 compared to channel 8 (1-3% higher accuracy). Reduction of the dimensions for the brain signals is effective in avoiding the local minimums. \begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline \multirow{2}{*}{**Subject**} & \multicolumn{2}{c}{**PSO**} & \multicolumn{2}{c}{**GA**} & \multicolumn{2}{c}{**BGA**} & \multicolumn{2}{c}{**QGA**} \\ \cline{2-9}  & \multicolumn{2}{c}{**FB 2 \& 5 \& 6} & \multicolumn{2}{c}{**FB 2 \& 5 \& 6} & \multicolumn{2}{c}{**FB 2 \& 5 \& 6} \\ \cline{2-9}  & \multicolumn{2}{c}{**Channel 8**} & \multicolumn{2}{c}{**Channel 12**} & \multicolumn{2}{c}{**Channel 8**} & \multicolumn{2}{c}{**Channel 12**} & \multicolumn{2}{c}{**Channel 8**} & \multicolumn{2}{c}{**Channel 12**} & \multicolumn{2}{c}{**Channel 8**} & \multicolumn{2}{c}{**Channel 12**} \\ \hline
1 & 60.7 & 60.9 & 62.42 & 63.32 & 61.1 & 60.9 & 62.2 & 61.5 \\
2 & **61.1** & 58.9 & 60.31 & 59.63 & **61.1** & **60.5** & 59.2 & 60.0 \\
3 & 60.6 & 61.7 & 60.86 & 62.25 & **61.5** & **63.5** & 59.9 & 61.4 \\
4 & **65.5** & 64.6 & 60.27 & 62.48 & 65.2 & **64.7** & 60.0 & 60.8 \\
5 & **61.5** & 62.2 & 59.52 & 63.03 & **61.4** & **62.5** & 58.0 & 61.8 \\
6 & **62.0** & 60.6 & 62.77 & 59.12 & 60.8 & **62.5** & 61.9 & 59.9 \\
7 & 60.6 & 64.3 & 61.90 & 65.66 & 60.0 & **66.2** & 60.0 & 65.3 \\
8 & 59.0 & 60.0 & 59.56 & 59.64 & **61.8** & **61.2** & 59.1 & 58.5 \\
9 & 59.6 & 61.1 & 60.43 & 62.31 & **61.1** & **63.0** & 60.2 & 61.3 \\ Ave & 61.2 & 61.6 & 60.89 & 61.86 & **61.6** & **62.8** & 60.1 & 61.2 \\ \hline \hline \end{tabular}
\end{table} 
Table 10: Feature selection accuracy of PSO, GA, and BGA with 100 features, FB2 & 5 & 6, and ELM for 100 iterations. \begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline \multirow{2}{*}{**Subject**} & \multicolumn{2}{c}{**PSO**} & \multicolumn{2}{c}{**GA**} & \multicolumn{2}{c}{**BGA**} & \multicolumn{2}{c}{**QGA**} \\ \cline{2-9}  & \multicolumn{2}{c}{**FB 2 \& 5**} & \multicolumn{2}{c}{**FB 2 \& 5**} & \multicolumn{2}{c}{**FB 2 \& 5**} & \multicolumn{2}{c}{**FB 2 \& 5**} \\ \cline{2-9}  & \multicolumn{2}{c}{**Channel 8**} & \multicolumn{2}{c}{**Channel 12**} & \multicolumn{2}{c}{**Channel 8**} & \multicolumn{2}{c}{**Channel 12**} & \multicolumn{2}{c}{**Channel 8**} & \multicolumn{2}{c}{**Channel 12**} & \multicolumn{2}{c}{**Channel 8**} & \multicolumn{2}{c}{**Channel 12**} \\ \hline
1 & 61.2 & 60.4 & 62.52 & 62.09 & 61.7 & 60.4 & **61.9** & **61.4** \\
2 & **62.6** & 59.8 & 59.53 & 59.44 & 61.1 & **60.2** & 58.3 & 58.6 \\
3 & 60.8 & 62.4 & 61.17 & 64.51 & **62.0** & **64.0** & 61.4 & 62.8 \\
4 & **66.5** & 65.0 & 62.76 & 61.45 & 65.1 & **65.1** & 62.2 & 60.7 \\
5 & 60.9 & 62.9 & 59.77 & 62.40 & **62.3** & **63.2** & 59.1 & 61.2 \\
6 & 61.1 & 61.3 & 62.27 & 60.04 & 59.9 & **61.6** & **61.5** & 60.1 \\
7 & 60.2 & 62.7 & 60.68 & 63.84 & 60.7 & **66.2** & 60.9 & 63.8 \\
8 & 57.4 & 58.8 & 59.4 & 60.78 & **60.7** & **62.4** & 56.8 & 58.7 \\
9 & 59.5 & 61.8 & 60.63 & 61.96 & 60.8 & **63.8** & **61.0** & 61.5 \\ Ave & 61.1 & 61.7 & 61.00 & 61.83 & **61.6** & **63.0** & 60.3 & 61.0 \\ \hline \hline \end{tabular}
\end{table}