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wiener_filter.tex
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wiener_filter.tex
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\input{prefix}
% =============================================================================
% =============================================================================
\begin{document}
% Signal model for Wiener filter
\begin{tikzpicture}[auto, node distance=2cm]
\node [input, name=input] {};
\node [block, right of=input,yshift=0cm] (system){\Large $G(e^{j \Omega})$};
\node [sum,right of=system, xshift=1cm] (sum){$+$};
\node [input, below of=sum,yshift=1cm] (noise) {};
\node [input, right of=sum, xshift=-1cm] (observation1) {};
\node [input, right of=observation1, xshift=-1.2cm] (observation) {};
\node [block, right of=observation,yshift=0cm] (filter){\Large $H(e^{j \Omega})$};
\node [output, right of=filter,xshift=0cm] (output) {};
\draw [-latex] (input) node[left]{$s[k]$} -- (system);
\draw [-latex] (system) -- (sum);
\draw [-latex] (sum) -- (observation1) node[right]{$x[k]$};
\draw [-latex] (observation) -- (filter);
\draw [-latex] (filter) -- (output) node[right]{$y[k]$};
\draw [-latex] (noise) node[below]{$n[k]$} -- (sum);
\draw [draw, dashed] (5.5, -2.0) -- (5.5, -.55);
\node at (2, -1.8) {Distortion};
\node at (8, -1.8) {Reconstruction};
\end{tikzpicture}
\end{document}