diff --git a/tex/chapters/conclusion.tex b/tex/chapters/conclusion.tex
index 99a667d..9d91c02 100644
--- a/tex/chapters/conclusion.tex
+++ b/tex/chapters/conclusion.tex
@@ -1,10 +1,19 @@
 \section{Conclusion}
+We presented a novel approach for integrating prior navigation knowledge by using realistic human walking paths. 
+Based on a weighted graph, two different models for walking in a more targeted and natural manner were introduced. 
+It could be shown that adding this additional knowledge causes an overall improvement of the localisation results, while maintaining flexible for uncertain behaviour. 
+Furthermore, our approach is able to provide accurate and robust position estimations, even when (normally) necessary calibration processes are ignored.
+
+However, providing this calibration knowledge can further improve the results. In order to reduce the effort of locating the \docAP{}s and calibrating them, a numerical optimization based on predefined walks could be considered. Additionally, the graph allows for storing pre-computed signal strengths and thus enables more complex prediction models incorporating floor and wall information into the signal strength estimation.
+
+As seen, multimodal distributions lead to faulty position estimations and therefore a rising error. One possible method to resolve this issue would be a more suiting location estimation method. Another promising way is smoothing. By deploying a fixed-lag smoother the system would still be perceived as real-time application, but is able to estimate the (delayed) estimation using future measurements up to the latest timestep.
 
 
-	\commentByFrank{balance zwischen den einzelnen wahrscheinlichkeiten ist oft ein schmaler grad. wieviel turn erlauben, wieviel auf den pfad zwingen. das verbesern}
-	\commentByFrank{position der APs wissen ist viel arbeit. vereinfachen durch test-walks auf vorgegebenen pfaden -> numerisch optimieren wo APs sind}
-	\commentByToni{quadtress. stellen die groesse der zellen variable ein. je nach bedarf.}
-	\commentByFrank{multimodalitaeten (z.B. treppenhaeuser). fixen durch andere estimations}
-	\commentByToni{oder durch smoothing}
-	\commentByToni{Aufzuege hinzufuegen. Vertical Acceleration benutzen.}
+
+%\commentByFrank{balance zwischen den einzelnen wahrscheinlichkeiten ist oft ein schmaler grad. wieviel turn erlauben, wieviel auf den pfad zwingen. das verbesern}
+%\commentByFrank{position der APs wissen ist viel arbeit. vereinfachen durch test-walks auf vorgegebenen pfaden -> numerisch optimieren wo APs sind}
+%\commentByToni{quadtress. stellen die groesse der zellen variable ein. je nach bedarf.}
+%\commentByFrank{multimodalitaeten (z.B. treppenhaeuser). fixen durch andere estimations}
+%\commentByToni{oder durch smoothing}
+%\commentByToni{Aufzuege hinzufuegen. Vertical Acceleration benutzen.}
 	
diff --git a/tex/chapters/system.tex b/tex/chapters/system.tex
index 8a2950c..c88c142 100644
--- a/tex/chapters/system.tex
+++ b/tex/chapters/system.tex
@@ -18,7 +18,7 @@
 	The hidden state $\mStateVec$ is given by
 	\begin{equation}
 		\mStateVec = (x, y, z, \mObsHeading, \mStatePressure),\enskip
-		x, y, z, \mObsHeading \mStatePressure \in \R \enspace,
+		x, y, z, \mObsHeading, \mStatePressure \in \R \enspace,
 	\end{equation}
 	%
 	where $x, y, z$ represent the position in 3D space, $\mObsHeading$ the user's heading and $\mStatePressure$ the