我的文章由两行组成。由于这个方程太长,我将其写成覆盖两列。但是,它仍然不适合。(5)溢出了。我该如何解决这个问题?
\documentclass[lettersize,journal]{IEEEtran}
\usepackage{amsmath,amsfonts}
\usepackage{algorithmic}
\usepackage{algorithm}
\usepackage{array}
\usepackage{algpseudocode}
\usepackage[caption=false,font=normalsize,labelfont=sf,textfont=sf]{subfig}
\usepackage{textcomp}
\usepackage{stfloats}
\usepackage{url}
\usepackage{stix}
\usepackage{verbatim}
\usepackage{graphicx}
\usepackage{cite}
\usepackage{color}
\usepackage{lipsum}
\usepackage{cuted}
\hyphenation{op-tical net-works semi-conduc-tor IEEE-Xplore}
\begin{document}
\begin{strip}
\begin{multline}
C(x,y,z,t) = \frac{m_T}{ (2\pi)^{3/2} \sigma_x \sigma_y \sigma_z}\times\text{exp}\left(-\frac{(x - x_T - u_x t)^2}{2\sigma_x^2} - \frac{(y - y_T - u_y t)^2}{2\sigma_y^2} \right)\times \left[ \text{exp}\left(-\frac{(z - z_T)^2}{2\sigma_z^2}\right) + \text{exp} \left( - \frac{(z + z_T)^2}{2\sigma_z^2} \right) \right].
\label{atm_disp_lang}
\end{multline}
\end{strip}
The advantage of this conversion is to determine the dispersion parameters ($\sigma_x$, $\sigma_y$, $\sigma_z$) by using empirically derived models which depend on the distance between the TX and RX.
\end{document}
答案1
我认为您不需要让它跨越两列,它没有那么大。
\documentclass[journal]{IEEEtran}
\usepackage{amsmath,amsfonts}
% \usepackage{algorithmic}
% \usepackage{algorithm}
% \usepackage{array}
% \usepackage{algpseudocode}
% \usepackage[caption=false,font=normalsize,labelfont=sf,textfont=sf]{subfig}
% \usepackage{textcomp}
%\usepackage{stfloats}
% \usepackage{url}
% \usepackage{stix}
% \usepackage{verbatim}
% \usepackage{graphicx}
% \usepackage{cite}
% \usepackage{color}
% \usepackage{lipsum}
\hyphenation{op-tical net-works semi-conduc-tor IEEE-Xplore}
\usepackage{kantlipsum}
\title{The Title}
\author{First Last}
\begin{document}
\maketitle
\section{The first section}
\begin{multline}
C(x,y,z,t)= \frac{m_T}{(2\pi)^{3/2} \sigma_x \sigma_y \sigma_z}
\times{}\\
\exp\biggl(
-\frac{(x - x_T - u_x t)^2}{2\sigma_x^2} - \frac{(y - y_T - u_y t)^2}{2\sigma_y^2}
\biggr)\times{}\\
\Biggl[
\exp\biggl(
-\frac{(z - z_T)^2}{2\sigma_z^2}
\biggr) + \exp\biggl(
- \frac{(z + z_T)^2}{2\sigma_z^2}
\biggr)
\Biggr].
\label{atm_disp_lang}
\end{multline}
The advantage of this conversion is to determine the dispersion parameters ($\sigma_x$, $\sigma_y$, $\sigma_z$) by using empirically derived models which depend on the distance between the TX and RX.
\kant[1-4]\kant[5][1-2]
\end{document}
(感谢 Celdor 提供的信息)
答案2
我会使用align
来分割你的等式,其中的“&”符号表示分割点的位置,并\\
表示换行符。请注意,align
左侧和右侧部分分别右对齐和左对齐。\phantom{={}}
只是为了在符号前面添加一些额外的空间\times
。
\begin{align}
C(x,y,z,t) &= \frac{m_T}{(2\pi)^{3/2} \sigma_x \sigma_y \sigma_z}
\times \exp{\biggl(
-\frac{(x - x_T - u_x t)^2}{2\sigma_x^2} - \frac{(y - y_T - u_y t)^2}{2\sigma_y^2}
\biggr)} \notag \\
&\phantom{={}}\;\times \Bigg[
\exp{\bigg(
{-}\frac{(z - z_T)^2}{2\sigma_z^2}
\biggr)} + \exp{\biggl(
{-}\frac{(z + z_T)^2}{2\sigma_z^2}
\biggr)}
\Bigg].
\label{atm_disp_lang}
\end{align}
您还应该避免使用自动缩放括号,而使用其固定替代方案,例如\bigl(...\bigr)
或\Biggl(...\Biggr)
等。
代码示例:
\documentclass[lettersize,journal]{IEEEtran}
\usepackage{amsmath,amsfonts}
% \usepackage{algorithmic}
% \usepackage{algorithm}
% \usepackage{array}
% \usepackage{algpseudocode}
% \usepackage[caption=false,font=normalsize,labelfont=sf,textfont=sf]{subfig}
% \usepackage{textcomp}
\usepackage{stfloats}
% \usepackage{url}
% \usepackage{stix}
% \usepackage{verbatim}
% \usepackage{graphicx}
% \usepackage{cite}
% \usepackage{color}
% \usepackage{lipsum}
\hyphenation{op-tical net-works semi-conduc-tor IEEE-Xplore}
\usepackage{kantlipsum}
\title{The Title}
\author{First Last}
\begin{document}
\maketitle
\section{The first section}
\begin{figure*}[b]
\begin{align}
C(x,y,z,t) &= \frac{m_T}{(2\pi)^{3/2} \sigma_x \sigma_y \sigma_z}
\times \exp{\biggl(
-\frac{(x - x_T - u_x t)^2}{2\sigma_x^2} - \frac{(y - y_T - u_y t)^2}{2\sigma_y^2}
\biggr)} \notag \\
&\phantom{={}}\;\times \Bigg[
\exp{\bigg(
{-}\frac{(z - z_T)^2}{2\sigma_z^2}
\biggr)} + \exp{\biggl(
{-}\frac{(z + z_T)^2}{2\sigma_z^2}
\biggr)}
\Bigg].
\label{atm_disp_lang}
\end{align}
\end{figure*}
The advantage of this conversion is to determine the dispersion parameters ($\sigma_x$, $\sigma_y$, $\sigma_z$) by using empirically derived models which depend on the distance between the TX and RX.
\kant[1-4]\kant[5][1-2]
\end{document}