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47 lines
1.9 KiB
TeX
47 lines
1.9 KiB
TeX
\begin{figure}
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\centering
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\begin{subfigure}[b]{0.49\textwidth}
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\centering
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\begin{adjustbox}{width=\textwidth, height=0.25\textheight}
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\begin{tikzpicture}
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\begin{axis}[tick style = {draw = none}, xticklabel = \empty,
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yticklabel=\empty]
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\addplot [mark options={scale = 0.7}, mark = o] table
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[x=x_d,y=y_d, col sep = comma] {Figures/Data/sin_conv.csv};
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\addplot [red, mark=x] table [x=x_i, y=y_i, col sep=comma, color ='black'] {Figures/Data/sin_conv.csv};
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\end{axis}
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\end{tikzpicture}
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\end{adjustbox}
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\caption{True position (\textcolor{red}{red}), distorted position data (black)}
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\end{subfigure}
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\hfill
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\begin{subfigure}[b]{0.49\textwidth}
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\centering
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\begin{adjustbox}{width=\textwidth, height=0.25\textheight}
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\begin{tikzpicture}
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\begin{axis}[tick style = {draw = none}, xticklabel = \empty,
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yticklabel=\empty]
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\addplot [mark options={scale = 0.7}, mark = o] table [x=x,y=y, col
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sep = comma] {Figures/Data/sin_conv.csv};
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\addplot [red, mark=x] table [x=x_i, y=y_i, col sep=comma, color ='black'] {Figures/Data/sin_conv.csv};
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\end{axis}
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\end{tikzpicture}
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\end{adjustbox}
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\caption{True position (\textcolor{red}{red}), filtered position data (black)}
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\end{subfigure}
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\caption[Signal Smoothing Using Convolution]{Example for noise reduction using convolution with simulated
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positional data. As filter
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$g(i)=\left(\nicefrac{1}{3},\nicefrac{1}{4},\nicefrac{1}{5},\nicefrac{1}{6},\nicefrac{1}{20}\right)_{(i-1)}$
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is chosen and applied to the $x$ and $y$ coordinate
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data separately. The convolution of both signals with $g$
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improves the MSE of the positions from 0.196 to 0.170 and
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visibly smoothes the data.
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}
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\label{fig:sin_conv}
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\end{figure}
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%%% Local Variables:
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%%% mode: latex
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%%% TeX-master: "../main"
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%%% End:
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