Created
July 12, 2010 14:42
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Good-looking HMM and Lattice diagrams using TikZ
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% (C) Mathieu Blondel, July 2010 | |
\documentclass[a4paper,10pt]{article} | |
\usepackage[english]{babel} | |
\usepackage[T1]{fontenc} | |
\usepackage[ansinew]{inputenc} | |
\usepackage{lmodern} | |
\usepackage{amsmath} | |
\usepackage{amsthm} | |
\usepackage{amsfonts} | |
\usepackage{tikz} | |
\begin{document} | |
\tikzstyle{state}=[shape=circle,draw=blue!50,fill=blue!20] | |
\tikzstyle{observation}=[shape=rectangle,draw=orange!50,fill=orange!20] | |
\tikzstyle{lightedge}=[<-,dotted] | |
\tikzstyle{mainstate}=[state,thick] | |
\tikzstyle{mainedge}=[<-,thick] | |
\begin{figure}[htbp] | |
\begin{center} | |
\begin{tikzpicture}[] | |
% states | |
\node[state] (s1) at (0,2) {$s_1$} | |
edge [loop above] (); | |
\node[state] (s2) at (2,2) {$s_2$} | |
edge [<-,bend right=45] node[auto,swap] {$a_{12}$} (s1) | |
edge [->,bend left=45] (s1) | |
edge [loop above] (); | |
\node[state] (s3) at (4,2) {$s_3$} | |
edge [<-,bend right=45] (s2) | |
edge [->,bend left=45] (s2) | |
edge [loop above] (); | |
\node[state] (s4) at (6,2) {$s_4$} | |
edge [<-,bend right=45] (s3) | |
edge [->,bend left=45] (s3) | |
edge [loop above] (); | |
% observations | |
\node[observation] (y1) at (2,0) {$y_1$} | |
edge [lightedge] (s1) | |
edge [lightedge] (s2) | |
edge [lightedge] (s3) | |
edge [lightedge] (s4); | |
\node[observation] (y2) at (4,0) {$y_2$} | |
edge [lightedge] (s1) | |
edge [lightedge] (s2) | |
edge [lightedge] (s3) | |
edge [lightedge] node[auto,swap] {$b_4(y_2)$} (s4); | |
\end{tikzpicture} | |
\end{center} | |
\caption{An HMM with 4 states which can emit 2 discrete symbols $y_1$ or $y_2$. | |
$a_{ij}$ is the probability to transition from state $s_i$ to state $s_j$. | |
$b_j(y_k)$ is the probability to emit symbol $y_k$ in state $s_j$. | |
In this particular HMM, states can only reach themselves or the adjacent state.} | |
\end{figure} | |
\begin{figure}[htbp] | |
\begin{center} | |
\begin{tikzpicture}[] | |
% 1st column | |
\node at (0,6) {$t=1$}; | |
\node[state] (s1_1) at (0,5) {$s_1$}; | |
\node[mainstate] (s2_1) at (0,4) {$s_2$}; | |
\node[state] (s3_1) at (0,3) {$s_3$}; | |
\node[state] (s4_1) at (0,2) {$s_4$}; | |
\node at (0,1) {$y_1$}; | |
% 2nd column | |
\node at (2,6) {$t=2$}; | |
\node[mainstate] (s1_2) at (2,5) {$s_1$} | |
edge[lightedge] (s1_1) | |
edge[mainedge] (s2_1) | |
edge[lightedge] (s3_1) | |
edge[lightedge] (s4_1); | |
\node[state] (s2_2) at (2,4) {$s_2$} | |
edge[lightedge] (s1_1) | |
edge[lightedge] (s2_1) | |
edge[lightedge] (s3_1) | |
edge[lightedge] (s4_1); | |
\node[state] (s3_2) at (2,3) {$s_3$} | |
edge[lightedge] (s1_1) | |
edge[lightedge] (s2_1) | |
edge[lightedge] (s3_1) | |
edge[lightedge] (s4_1); | |
\node[state] (s4_2) at (2,2) {$s_4$} | |
edge[lightedge] (s1_1) | |
edge[lightedge] (s2_1) | |
edge[lightedge] (s3_1) | |
edge[lightedge] (s4_1); | |
\node at (2,1) {$y_2$}; | |
% 3rd column | |
\node at (4,6) {$t=3$}; | |
\node[mainstate] (s1_3) at (4,5) {$s_1$} | |
edge[mainedge] (s1_2) | |
edge[lightedge] (s2_2) | |
edge[lightedge] (s3_2) | |
edge[lightedge] (s4_2); | |
\node[state] (s2_3) at (4,4) {$s_2$} | |
edge[lightedge] (s1_2) | |
edge[lightedge] (s2_2) | |
edge[lightedge] (s3_2) | |
edge[lightedge] (s4_2); | |
\node[state] (s3_3) at (4,3) {$s_3$} | |
edge[lightedge] (s1_2) | |
edge[lightedge] (s2_2) | |
edge[lightedge] (s3_2) | |
edge[lightedge] (s4_2); | |
\node[state] (s4_3) at (4,2) {$s_4$} | |
edge[lightedge] (s1_2) | |
edge[lightedge] (s2_2) | |
edge[lightedge] (s3_2) | |
edge[lightedge] (s4_2); | |
\node at (4,1) {$y_2$}; | |
\end{tikzpicture} | |
\end{center} | |
\caption{Trellis of the observation sequence $y_1$,$y_2$,$y_2$ for the above HMM. The thick arrows | |
indicate the most probable transitions. As an example, the transition | |
between state $s_1$ at time t=2 and state $s_4$ at time t=3 has probability | |
$\alpha_2(1)a_{14}b_4(y_2)$, where $\alpha_t(i)$ is the probability to be in | |
state $s_i$ at time t.} | |
\end{figure} | |
\end{document} |
Thanks!
thank s man
Great !
Thanks for sharing
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Awesome. Thanks