latex算法排版


下給出使用latex進行算法排版的幾個例子,以供參考:

 

 

 

 

 

\documentclass{article}

\usepackage[english]{babel}

\usepackage{blindtext}

\usepackage{algorithm} %format of the algorithm

\usepackage{algorithmic} %format of the algorithm

<?xml:namespace prefix = o /> 

\begin{document}

\blindtext

 

\begin{algorithm}[htb] %算法的開始

\renewcommand{\algorithmicrequire}{\textbf{Input:}}

\renewcommand\algorithmicensure {\textbf{Output:} }

\caption{ Framework of ensemble learning for our system.} %算法的標題

\label{alg:Framwork} %給算法一個標簽,這樣方便在文中對算法的引用

\begin{algorithmic}[1] %這個1 表示每一行都顯示數字

\REQUIRE ~~\\ %算法的輸入參數:Input

The set of positive samples for current batch, $P_n$;\\

The set of unlabelled samples for current batch, $U_n$;\\

Ensemble of classifiers on former batches, $E_{n-1}$;

\ENSURE ~~\\ %算法的輸出:Output

Ensemble of classifiers on the current batch, $E_n$;\\

\STATE Extracting the set of reliable negative and/or positive samples $T_n$ from $U_n$ with help of $P_n$; label{code:fram:extract} %算法的一個陳述,對應算法的一個步驟或公式之類的; label{ code:fram:extract }對此行的標記,方便在文中引用算法的某個步驟

\STATE Training ensemble of classifiers $E$ on $T_n cup P_n$, with help of data in former batches; label{code:fram:trainbase}

\STATE $E_n=E_{n-1}cup E$; label{code:fram:add}

\STATE Classifying samples in $U_n-T_n$ by $E_n$; label{code:fram:classify}

\STATE Deleting some weak classifiers in $E_n$ so as to keep the capacity of $E_n$; label{code:fram:select}

\RETURN $E_n$; %算法的返回值

\end{algorithmic}

\end{algorithm}

 

\blindtext

\end{document}

=====

2.

\documentclass{article}

 

\usepackage[english]{babel}

\usepackage{blindtext}

\usepackage{algorithm} %format of the algorithm

\usepackage{algorithmic} %format of the algorithm

 

\begin{document}

\blindtext

\begin{algorithm}[h]

\caption{An example for format For While Loop in Algorithm}

\begin{algorithmic}[1]

\FOR{each $iin [1,9]$}

\STATE initialize a tree $T_{i}$ with only a leaf (the root);\

\STATE $T_{i};$\

\ENDFOR

\FOR{$i=1$; $i<n$; $i++$ }

\STATE $//$ Your source here;

\ENDFOR

\WHILE {$(|E_n| leq L_1 )and(Deq phi)$}

\STATE Selecting the most recent classifier $c_i$ from $D$;

\STATE $D=D-c_i$;

\STATE $E_n=E_n+c_i$;

\ENDWHILE \label{code:recentEnd}

\end{algorithmic}

\end{algorithm}

 

\blindtext

\end{document}

===========



 轉:http://hi.baidu.com/chong_jing/item/1e6a9832c05bf0352f0f817f


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