IEEE投稿之Latex笔记

1. 表格1(单栏没有*)

\begin{table*}%[htbp] %htbp为位置控制
	\caption{Recognition rates (mean $\pm$ std\%) of different methods on the USPS dataset}
	\centering
	\begin{tabular}{lllllll}
		\toprule
		&
		\multicolumn{3}{c}{Silver Bullet Method} &
		\multicolumn{3}{c}{Werewolf Method} \\
		\InvB & \one & \two & \three & \one & \two & \three\\ % They are cells!!!! see the preambles to check the cell definitions!
		\midrule
		\TranExp & \TCo & \TCt & \TCth & \TCo & \TDt & \TDth \\[0.22cm].  
		\GenExp & \GCo & \GCt & \GCth & \GCo & \GDt & \GDth \\[0.22cm]
		\TotalCost & \TcoC & \TctC & \TcthC & \TcoD & \TctD & \TcthD\\[0.22cm]
		\LoL & \LoLoC & \LoLtC & \LoLthC & \LoLoD & \LoLtD & \LoLthD \\[0.22cm] 
		\IterNum & \InoC & \IntC & \InthC & \InoD & \IntD & \InthD\\[0.22cm]
		\WallTime & \WtoC &\WttC &\WtthC & \WtoD &\WttD & \WtthD \\
		\bottomrule
	\end{tabular}
\end{table*}

2. 表格2(单栏没有*)

\begin{table}[!t]
	\renewcommand{\arraystretch}{1.3}
	\caption{Recognition rates (mean $\pm$ std\%) of different methods on the USPS dataset}
	\label{table_example}
	\centering
	\begin{tabular}{|p{4.6em}|p{4.6em}|p{4.6em}|p{4.6em}|p{4.6em}|}
		\hline
		\centering
		Alg.& 20 & 40 & 80 & 100          \\
		\hline\hline
		\centering
		SRC  	& 88.25±0.92   & 88.25±0.92            & 88.25±0.92      & 88.25±0.92        \\
		\centering
		KSVD  	& 88.25±0.92   & 88.25±0.92            & 88.25±0.92      & 88.25±0.92        \\
		\centering
		D-KSVD  & 88.25±0.92   & 88.25±0.92            & 88.25±0.92      & 88.25±0.92        \\
		\centering
		LC-KSVD & 88.25±0.92   & 88.25±0.92            & 88.25±0.92      & 88.25±0.92        \\
		\centering
		DLSPC   & 88.25±0.92   & 88.25±0.92            & 88.25±0.92      & 88.25±0.92        \\
		\centering
		FDDL    & 88.25±0.92   & 88.25±0.92            & 88.25±0.92      & 88.25±0.92        \\
		\centering
		SVGDL   & 88.25±0.92   & 88.25±0.92            & 88.25±0.92      & 88.25±0.92        \\
		\centering
		BDLRR   & 88.25±0.92   & 88.25±0.92            & 88.25±0.92      & 88.25±0.92        \\		
		\centering
		ASF-SRC & 88.25±0.92   & 88.25±0.92            & 88.25±0.92      & 88.25±0.92        \\	
		\centering
        \bfseries GEBDDL  & 88.25±0.92   & 88.25±0.92            & 88.25±0.92      & 88.25±0.92        \\
		\centering
		\bfseries MPDDDL  & 88.25±0.92   & 88.25±0.92            & 88.25±0.92      & 88.25±0.92        \\				
		\hline
	\end{tabular}
\end{table}

3. 表格双栏(双栏有*)

\begin{table*}%[htbp] %htbp为位置控制
	\caption{Recognition rates (mean $\pm$ std\%) of different methods on the USPS dataset}
	\centering
	\begin{tabular}{lllllll}
		\toprule
		&
		\multicolumn{3}{c}{Silver Bullet Method} &
		\multicolumn{3}{c}{Werewolf Method} \\
		\InvB & \one & \two & \three & \one & \two & \three\\ % They are cells!!!! see the preambles to check the cell definitions!
		\midrule
		\TranExp & \TCo & \TCt & \TCth & \TCo & \TDt & \TDth \\[0.22cm].  
		\GenExp & \GCo & \GCt & \GCth & \GCo & \GDt & \GDth \\[0.22cm]
		\TotalCost & \TcoC & \TctC & \TcthC & \TcoD & \TctD & \TcthD\\[0.22cm]
		\LoL & \LoLoC & \LoLtC & \LoLthC & \LoLoD & \LoLtD & \LoLthD \\[0.22cm] 
		\IterNum & \InoC & \IntC & \InthC & \InoD & \IntD & \InthD\\[0.22cm]
		\WallTime & \WtoC &\WttC &\WtthC & \WtoD &\WttD & \WtthD \\
		\bottomrule
	\end{tabular}
\end{table*}

4. 图形(双栏有*)

\vspace{0.5cm}
\begin{figure*}      
	\begin{minipage}{0.5\textwidth}  %% {0.18\textwidth}
		\centerline{\includegraphics[width=0.85\textwidth]{loss.pdf}}
		\centerline{\small{(a) Convergence comparison}}
	\end{minipage}
	\hfill
	\begin{minipage}{0.5\textwidth}  %% {0.90\textwidth}
		\centerline{\includegraphics[width=0.85\textwidth]{acc.pdf}}
		\centerline{\small{(b) Recognition rates versus iterations}}
	\end{minipage}
	\hfill
	\caption{\small{Convergence comparison and recognition comparison versus iterations on the Extended Yale B dataset.}}
	\label{fig:1}
\end{figure*}
\vspace{-1cm}

5. 算法

\usepackage{algorithm, algorithmicx}		% For presenting algorithms

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% Algorithm 2
\begin{algorithm}%[H]
	% Exercise: Try to remove [H] and see what's gonna happen :P
	% Answer: [H] means stick to the position. 
	\caption{Maximum pairwise distance guided discriminative dictionary learning (MPDDDL)}
	\begin{algorithmic}
		\State \textbf{Input:} The training samples $\mathcal{D}=\left\{\mathbf{x}_{i} | i=1, \dots, N\right\}$, parameters $\lambda_{1}, \lambda_{2}$ and $\theta$, the maximum number of iterations $T$, and the threshold $\sigma$ that denotes minimal difference in norm between dictionary $\mathbf{D}^{j}$ and $\mathbf{D}^{j+1}$.
		\State \textbf{Output:} The learned dictionary matrix $\bf D$ and the hyperplane parameters $\{\hat{\mathbf{w}}_{c}, \hat{\bf{b}}_{c}) | c=1, \ldots, C\}$. 
		\State \textbf{Initialize:} the dictionary matrix $\bf D$ and the coding vector matrix $\bf S$.
		\State \text{1:} \textbf{Repeat} 
		\State \text{2:} \qquad \textbf{Compute} $\widetilde{D}$ with (37);
		\State \text{3:} \qquad \textbf{Compute} the partial derivatives (23);
		\State \text{4:} \qquad \textbf{Update} $\{\hat{\mathbf{w}}_{c}, \hat{\bf{b}}_{c}) | c=1, \ldots, \}$ by employing a \\ \qquad \;\;\; gradient descent method;
		\State \text{5:} \qquad \textbf{Compute} the partial derivatives (45);
		\State \text{6:} \qquad \textbf{Update} $\bf S$ by employing a gradient descent method;
		\State \text{7:} \qquad \textbf{Update} D with (33);
		\State \text{8:} \textbf{Until} $\frac{\text{norm}\left(\mathbf{D}^{j+1}-\mathbf{D}^{j}\right)}{\text{norm}\left(\mathbf{D}^{j+1}\right)}<\sigma$ or $j>T$
		\State \text{9:} \textbf{Return} the learned dictionary matrix $\bf D$ and the hyper-\\ \; \, plane parameters $\{\hat{\mathbf{w}}_{c}, \hat{\bf{b}}_{c}) | c=1,..., C\}$.
	\end{algorithmic}
\end{algorithm}

6. 公式等号对齐

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%   27
\begin{equation}
\begin{aligned}
\tilde D &= \sqrt {\mathop {\max }\limits_{i,j} ||{{{\tilde{\bf s}}}_i} - {{{\tilde{\bf s}}}_j}|{|^2}} {}\\
&=\sqrt {\mathop {\max }\limits_{i \ne j} \left( {{\bf{s}}_i^T{{\bf{s}}_i} + {\bf{s}}_j^T{{\bf{s}}_j} - 2{\bf{s}}_i^T{{\bf{s}}_j}} \right) + \frac{1}{\theta }} 
\end{aligned}
\label{f2}	
\end{equation}

7. 补充算法

7.1. 方式1

• 需要包含如下包：

\usepackage{algorithm, algorithmicx, algorithmic}

\begin{algorithm}[t]
	\caption{Metric Learning Based on Intrinsic Structural Characteristic of Data} %算法的名字
	{\bf Input:} 
	The training set ${\rm{\{ }}({{\bf{x}}_i},{y_i}){\rm{|}}i = 1,2,...,n{\rm{\} ,}}{{\bf{x}}_i} \in {{\bf{R}}^m}$\\
	{\bf Output:} 
	The learned metric matrix $\bf M$.
	\begin{algorithmic}[1]
		\State \textbf{Initialize:} the dictionary matrix $\bf D$ and the coding matrix $\bf S$; 
		\Repeat
		\While{the stopping criterion is not met}
		\If{${l_i}({{\bf{w}}^T}{\bf{\tilde x}} + b) < 1$} 
		\State \textbf{Calculate} the partial derivatives $\frac{{\partial {\cal L}({\bf{w}},b)}}{{\partial \bf{w}}}$ and \hspace*{0.36in} $\frac{{\partial {\cal L}({\bf{w}},b)}}{{\partial b}}$ with (15);
		\Else
		\State \textbf{Calculate} the partial derivatives $\frac{{\partial {\cal L}({\bf{w}},b)}}{{\partial \bf{w}}}$ and \hspace*{0.36in} $\frac{{\partial {\cal L}({\bf{w}},b)}}{{\partial b}}$ with (17);
		\EndIf
		\State \textbf{end if}
		\State \textbf{Update} $\bf{w}$ and $b$ by employing a gradient descent \hspace*{0.17in} method;
		\State \textbf{Update} the metric matrix with (22) according to the \hspace*{0.22in}solution of (18);
		\State $t = t + 1$;
		\EndWhile
		\Until{b}
		\State \textbf{end while}
		\State \Return The learned metric matrix $\bf M$.
	\end{algorithmic}
\end{algorithm}

• 注意
• 关键字的大小写问题，否则会出现 Undefined control sequence.
• 控制流要前后对应。如果有 While，但没有 EndWhile，否则会出现 Some blocks are not closed。

7.1. 方式2

• 需要包含如下包：

\usepackage[ruled]{algorithm2e}

\begin{algorithm}[H]
\caption{algorithm caption}%算法名字
\LinesNumbered %要求显示行号
\KwIn{input parameters A, B, C}%输入参数
\KwOut{output result}%输出
some description\; %\;用于换行
\For{condition}{
　　only if\;
　　\If{condition}{
　　　　1\;
　　}
}
\While{not at end of this document}{
　　if and else\;
　　\eIf{condition}{
　　　　1\;
　　}{
　　　　2\;
　　}
}
\ForEach{condition}{
　　\If{condition}{
　　　　1\;
　　}
}
\end{algorithm}

7.3. 方式3

• 需要包含如下包：

\usepackage[ruled,vlined]{algorithm2e}

• 源码同方式二

参考文章

• LaTeX算法表格(重要)
• LaTeX外部模板（IEEEtrans）初次套用经历
• LaTeX算法排版