我正准备第一次将文章投递给 Springer 期刊。我有一个很长的算法要写在论文中，如何让算法在到达模板定义的边距时自动分成多列？
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\usepackage{graphicx}
\usepackage{graphics}
\usepackage{refstyle}
\usepackage{amsfonts}
\usepackage{amstext}
\usepackage{amsmath}
\usepackage{amssymb}
\usepackage{enumerate}
\usepackage{epstopdf}
\usepackage{breqn}
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\usepackage{newlfont}
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\usepackage{algorithm}
\usepackage{algpseudocode}
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% \newcommand{}{}
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% \journalname{myjournal}
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\begin{document}
\title{Insert your title here%\thanks{Grants or other notes
%about the article that should go on the front page should be
%placed here. General acknowledgments should be placed at the end of the article.}
}
\subtitle{Do you have a subtitle?\\ If so, write it here}
%\titlerunning{Short form of title} % if too long for running head
\author{First Author \and
Second Author %etc.
}
%\authorrunning{Short form of author list} % if too long for running head
\institute{F. Author \at
first address \\
Tel.: +123-45-678910\\
Fax: +123-45-678910\\
\email{[email protected]} % \\
% \emph{Present address:} of F. Author % if needed
\and
S. Author \at
second address
}
\date{Received: date / Accepted: date}
% The correct dates will be entered by the editor
\maketitle
\begin{abstract}
Insert your abstract here. Include keywords, PACS and mathematical
subject classification numbers as needed.
\keywords{First keyword \and Second keyword \and More}
% \PACS{PACS code1 \and PACS code2 \and more}
% \subclass{MSC code1 \and MSC code2 \and more}
\end{abstract}
\section{Introduction}
\label{intro}
Your text comes here. Separate text sections with
\section{Section title}
\label{sec:1}
Text with citations \cite{RefB} and \cite{RefJ}.
%-----------------------------------------------------------------------------------------------
\begin{algorithm}
\caption{Square Root Cubature Kalman Filter (SCKF)}
\textbf{Time update}
\begin{algorithmic}[1]
\State Evaluate the cubature points (i=1,2,...,$m = 2n_x$)
\begin{equation}
X_{i,k-1|k-1} = \hat{x}_{k-1|k-1} + S_{i,k-1|k-1}\zeta_i
\label{eq:Ref_3}
\end{equation}
\State Evaluate the propagated cubature points through the process equation (i=1,2,...,$m = 2n_x$)
\begin{equation}
X_{i,k|k-1}^*=f(X_{i,k-1|k-1},u_{k-1},\theta)
\label{eq:Ref_3}
\end{equation}
\State Estimate the predicted state
\begin{equation}
\hat{x}_{k|k-1} = \frac{1}{m}\sum_{i=1}^m{X_{i,k|k-1}^*}Y
\label{eq:Ref_3}
\end{equation}
\State Estimate the square root factor of the predicted error covariance.
\begin{equation}
S_{k|k-1} = Tria([\chi_{k|k-1}^* S_{Q,k-1}])
\label{eq:Ref_3}
\end{equation}
Where $S_{Q,k-1}$ denote the square root factor of $Q_{k-1}$ such that $Q_{k-1} = S_{Q,k-1}S_{Q,k-1}^T $, and the weighted centered matrix:
\begin{equation}
\chi_{k|k-1}^* = \frac{1}{\sqrt{m}}\left[ X_{1,k|k-1}^*-\hat{x}_{k|k-1} \cdots X_{m,k|k-1}^*-\hat{x}_{k|k-1})\right]
\label{eq:Ref_3}
\end{equation}
\textbf{Measurement update}
\State Evaluate the cubature point (i=1,2,...,m)
\begin{equation}
X_{i,k|k-1} = \hat{x}_{k|k-1} + S_{k|k-1}\zeta_i
\label{eq:Ref_3}
\end{equation}
\State Evaluate the propagated cubature point through the measurement equation
\begin{equation}
Y_{i,k|k-1} = h(X_{i,k|k-1})
\label{eq:Ref_3}
\end{equation}
\State Estimate the predicted measurement
\begin{equation}
\hat{y}_{k|k-1} = \frac{1}{m}\sum_{i=1}^m{Y_{i,k|k-1}}
\label{eq:Ref_3}
\end{equation}
\State Estimate the square root of the innovation covariance matrix.
\begin{equation}
S_{yy,k|k-1} = Tria(YZ_{k|k-1} S_{R,k}])
\label{eq:Ref_3}
\end{equation}
Where $S_{R,k}$ denote the square root factor of $R_k$ such that $R_k = S_{R,k}S_{R,k}^T $ and the weighted centered matrix:
\begin{equation}
Y_{k|k-1} = \frac{1}{\sqrt{m}}\left[ Y_{1,k|k-1}-\hat{y}_{k|k-1} \cdots Y_{m,k|k-1}-\hat{y}_{k|k-1})\right]
\label{eq:Ref_3}
\end{equation}
\State Estimate the cross-covariance matrix
\begin{equation}
P_{xz,k|k-1} = \chi_{k|k-1}Y_{k|k-1}^T
\label{eq:Ref_3}
\end{equation}
Where the weighted, centered matrix $\chi_{k|k-1}$ is defined by
\begin{equation}
\chi_{k|k-1} = \frac{1}{\sqrt{m}}\left[ X_{1,k|k-1}-\hat{x}_{k|k-1} \cdots X_{m,k|k-1}-\hat{x}_{k|k-1})\right]
\label{eq:Ref_3}
\end{equation}
\State Estimate the Kalman gain
\begin{equation}
K_k = (P_{xy,k|k-1}/S_{yy,k|k-1}^T)/S_{yy,k|k-1}^T)
\label{eq:Ref_3}
\end{equation}
\State Estimate the updated state
\begin{equation}
\hat{x}_{k|k}=\hat{x}_{k|k-1}+K_k(y_k-\hat{y}_{k|k-1})
\label{eq:Ref_2}
\end{equation}
\State Estimate the square root factor of the corresponding error covariance.
\begin{equation}
S_{k|k} = Tria([\chi_{k|k-1} - K_k Y_{k|k-1}...K_k R_{R,k}]
\label{eq:Ref_3}
\end{equation}
\end{algorithmic}
\end{algorithm}
%------------------------------------------------------------------------------------------------------
\subsection{Subsection title}
\label{sec:2}
as required. Don't forget to give each section
and subsection a unique label (see Sect.~\ref{sec:1}).
\paragraph{Paragraph headings} Use paragraph headings as needed.
\begin{equation}
a^2+b^2=c^2
\end{equation}
% For one-column wide figures use
\begin{figure}
% Use the relevant command to insert your figure file.
% For example, with the graphicx package use
\includegraphics{example.eps}
% figure caption is below the figure
\caption{Please write your figure caption here}
\label{fig:1} % Give a unique label
\end{figure}
%
% For two-column wide figures use
\begin{figure*}
% Use the relevant command to insert your figure file.
% For example, with the graphicx package use
\includegraphics[width=0.75\textwidth]{example.eps}
% figure caption is below the figure
\caption{Please write your figure caption here}
\label{fig:2} % Give a unique label
\end{figure*}
%
% For tables use
\begin{table}
% table caption is above the table
\caption{Please write your table caption here}
\label{tab:1} % Give a unique label
% For LaTeX tables use
\begin{tabular}{lll}
\hline\noalign{\smallskip}
first & second & third \\
\noalign{\smallskip}\hline\noalign{\smallskip}
number & number & number \\
number & number & number \\
\noalign{\smallskip}\hline
\end{tabular}
\end{table}
%\begin{acknowledgements}
%If you'd like to thank anyone, place your comments here
%and remove the percent signs.
%\end{acknowledgements}
% BibTeX users please use one of
%\bibliographystyle{spbasic} % basic style, author-year citations
%\bibliographystyle{spmpsci} % mathematics and physical sciences
%\bibliographystyle{spphys} % APS-like style for physics
%\bibliography{} % name your BibTeX data base
% Non-BibTeX users please use
\begin{thebibliography}{}
%
% and use \bibitem to create references. Consult the Instructions
% for authors for reference list style.
%
\bibitem{RefJ}
% Format for Journal Reference
Author, Article title, Journal, Volume, page numbers (year)
% Format for books
\bibitem{RefB}
Author, Book title, page numbers. Publisher, place (year)
% etc
\end{thebibliography}
\end{document}
% end of file template.tex
答案1
删除algorithm环境并将标题改为节标题。另一方面，我认为您实际上并不需要环境algorithmic。
\RequirePackage{fix-cm}
%
\documentclass[twocolumn]{svjour3} % twocolumn
\usepackage{mathptmx}
\usepackage{amsmath}
\usepackage{lipsum} % for mock text
\newcounter{resume}
\DeclareMathOperator{\Tria}{Tria}
\begin{document}
\title{Title}
\subtitle{Subtitle}
%\titlerunning{Short form of title} % if too long for running head
\author{First Author \and Second Author}
%\authorrunning{Short form of author list} % if too long for running head
\institute{F. Author \at
first address \\
Tel.: +123-45-678910\\
Fax: +123-45-678910\\
\email{[email protected]} % \\
% \emph{Present address:} of F. Author % if needed
\and
S. Author \at
second address
}
\date{Received: date / Accepted: date}
% The correct dates will be entered by the editor
\maketitle
\begin{abstract}
Insert your abstract here. Include keywords, PACS and mathematical
subject classification numbers as needed.
\keywords{First keyword \and Second keyword \and More}
% \PACS{PACS code1 \and PACS code2 \and more}
% \subclass{MSC code1 \and MSC code2 \and more}
\end{abstract}
\section{Introduction}
\label{intro}
\lipsum[1-2]
\section{Section title}
\label{sec:1}
Text with citations \cite{RefB} and \cite{RefJ}.
\lipsum[3-4]
\section{Square Root Cubature Kalman Filter (SCKF)}
\subsection*{Time update}
\begin{enumerate}
\item Evaluate the cubature points ($i=1,2,\dots,m =\nobreak 2n_x$)
\begin{equation}
X_{i,k-1|k-1} = \hat{x}_{k-1|k-1} + S_{i,k-1|k-1}\zeta_i
\label{eq:Ref_1}
\end{equation}
\item Evaluate the propagated cubature points through the process equation ($i=1,2,\dots,m = 2n_x$)
\begin{equation}
X_{i,k|k-1}^*=f(X_{i,k-1|k-1},u_{k-1},\theta)
\label{eq:Ref_2}
\end{equation}
\item Estimate the predicted state
\begin{equation}
\hat{x}_{k|k-1} = \frac{1}{m}\sum_{i=1}^m{X_{i,k|k-1}^*}Y
\label{eq:Ref_3}
\end{equation}
\item Estimate the square root factor of the predicted error covariance.
\begin{equation}
S_{k|k-1} = \Tria([\chi_{k|k-1}^* S_{Q,k-1}])
\label{eq:Ref_4}
\end{equation}
Where $S_{Q,k-1}$ denote the square root factor of $Q_{k-1}$ such that $Q_{k-1} = S_{Q,k-1}S_{Q,k-1}^T $, and the weighted centered matrix:
\begin{equation}
\chi_{k|k-1}^* = \frac{1}{\sqrt{m}}\left[ X_{1,k|k-1}^*-\hat{x}_{k|k-1} \dots X_{m,k|k-1}^*-\hat{x}_{k|k-1})\right]
\label{eq:Ref_5}
\end{equation}
\setcounter{resume}{\value{enumi}}
\end{enumerate}
\subsection*{Measurement update}
\begin{enumerate}
\setcounter{enumi}{\value{resume}}
\item Evaluate the cubature point (i=1,2,\dots,m)
\begin{equation}
X_{i,k|k-1} = \hat{x}_{k|k-1} + S_{k|k-1}\zeta_i
\label{eq:Ref_6}
\end{equation}
\item Evaluate the propagated cubature point through the measurement equation
\begin{equation}
Y_{i,k|k-1} = h(X_{i,k|k-1})
\label{eq:Ref_7}
\end{equation}
\item Estimate the predicted measurement
\begin{equation}
\hat{y}_{k|k-1} = \frac{1}{m}\sum_{i=1}^m{Y_{i,k|k-1}}
\label{eq:Ref_8}
\end{equation}
\item Estimate the square root of the innovation covariance matrix.
\begin{equation}
S_{yy,k|k-1} = \Tria(YZ_{k|k-1} S_{R,k}])
\label{eq:Ref_9}
\end{equation}
Where $S_{R,k}$ denote the square root factor of $R_k$ such that $R_k = S_{R,k}S_{R,k}^T $ and the weighted centered matrix:
\begin{equation}
Y_{k|k-1} = \frac{1}{\sqrt{m}}\left[ Y_{1,k|k-1}-\hat{y}_{k|k-1} \dots Y_{m,k|k-1}-\hat{y}_{k|k-1})\right]
\label{eq:Ref_10}
\end{equation}
\item Estimate the cross-covariance matrix
\begin{equation}
P_{xz,k|k-1} = \chi_{k|k-1}Y_{k|k-1}^T
\label{eq:Ref_11}
\end{equation}
Where the weighted, centered matrix $\chi_{k|k-1}$ is defined by
\begin{equation}
\chi_{k|k-1} = \frac{1}{\sqrt{m}}\left[ X_{1,k|k-1}-\hat{x}_{k|k-1} \dots X_{m,k|k-1}-\hat{x}_{k|k-1})\right]
\label{eq:Ref_12}
\end{equation}
\item Estimate the Kalman gain
\begin{equation}
K_k = (P_{xy,k|k-1}/S_{yy,k|k-1}^T)/S_{yy,k|k-1}^T)
\label{eq:Ref_13}
\end{equation}
\item Estimate the updated state
\begin{equation}
\hat{x}_{k|k}=\hat{x}_{k|k-1}+K_k(y_k-\hat{y}_{k|k-1})
\label{eq:Ref_14}
\end{equation}
\item Estimate the square root factor of the corresponding error covariance.
\begin{equation}
S_{k|k} = \Tria([\chi_{k|k-1} - K_k Y_{k|k-1}\dots K_k R_{R,k}]
\label{eq:Ref_15}
\end{equation}
\end{enumerate}
\section{Whatever}
\lipsum[1-4]
\begin{thebibliography}{}
\bibitem{RefJ}
% Format for Journal Reference
Author, Article title, Journal, Volume, page numbers (year)
% Format for books
\bibitem{RefB}
Author, Book title, page numbers. Publisher, place (year)
% etc
\end{thebibliography}
\end{document}
% end of file template.tex
