Add table of execution time

1 files changed, 18 insertions, 1 deletions

diff --git a/report/paper.md b/report/paper.md
index bcb2386..f3b3584 100755
--- a/report/paper.md
+++ b/report/paper.md
@@ -73,7 +73,7 @@ and the there is a relation between the eigenvectors obtained: $\boldsymbol{u\te
 
 Experimentally there is no consequential loss of data calculating the eigenvectors
 for PCA when using the low dimensional method. The main advantages of it are reduced computation time,
-(since the two methods require on average respectively 3.4s and 0.11s), and complexity of computation
+(since the two methods require on average respectively 3.7s and 0.11s), and complexity of computation
 (since the eigenvectors found with the first method are extracted from a significantly 
 bigger matrix).
 
@@ -506,6 +506,23 @@ We know that $S\boldsymbol{u\textsubscript{i}} = \lambda \textsubscript{i}\bolds
  
 From here it follows that AA\textsuperscript{T} and A\textsuperscript{T}A have the same eigenvalues and their eigenvectors follow the relationship $\boldsymbol{u\textsubscript{i}} = A\boldsymbol{v\textsubscript{i}}$ 
 
+### Table of execution times of different methods
+
+\begin{table}[ht]
+\centering
+\begin{tabular}[t]{l|lll} 
+\hline
+	& Best(s)	& Worst(s) 	& Average(s)	\\ \hline
+PCA 	& 3.5		& 3.8		& 3.7		\\
+PCA-F 	& 0.10		& 0.24		& 0.11		\\
+PCA-ALT & 1.0		& 1.3		& 1.1		\\
+LDA 	& 5.0		& 5.8		& 5.2		\\
+LDA-PCA & 0.11		& 0.19		& 0.13		\\ \hline
+\end{tabular}
+\caption{Comparison of execution times between different methods}
+\label{tab:time}
+\end{table}
+
 ## Code
 
 All code and \LaTeX sources are available at: