Nanjing University thesis (njuthesis)

% 南京大学学位论文 / Nanjing University thesis on njuthesis.cls. Build with XeLaTeX and biber.
% type = bachelor | master | doctor | postdoc; degree = academic | professional.
% fontset = fandol uses the Fandol and TeX Gyre fonts in TeX Live; switch to fontset = win
% when the Windows fonts are available. The class loads biblatex (GB/T 7714-2015) itself.
\documentclass[type=master,degree=academic,fontset=fandol]{njuthesis}

\njusetup{
  info = {
    title         = {Your paper},
    title*        = {Your paper},
    keywords      = {信息论, 熵, 学位论文},
    keywords*     = {information theory, entropy, thesis},
    grade         = {2024},
    student-id    = {000000000},
    author        = {作者姓名},
    author*       = {Author Name},
    department    = {某某学院},
    department*   = {School of Example Studies},
    major         = {计算机科学与技术},
    major*        = {Computer Science and Technology},
    field         = {信息论},
    field*        = {Information Theory},
    supervisor    = {导师姓名, 教授},
    supervisor*   = {Professor Supervisor Name},
    submit-date   = {2027-05-20},
    defend-date   = {2027-06-01},
    clc           = {TP301},
    udc           = {004},
    secret-level  = {公开},
    chairman      = {主席姓名~教授},
    reviewer      = {委员姓名~教授, 委员姓名~副教授},
  },
  bib/resource = {references.bib},
}

\usepackage{tikz}

% The class draws the university emblem and name on the covers (package njuvisual) unless
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% delete the two lines below to draw them.
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\NewDocumentCommand \njuname   { o m m } { {\zihao{1}\bfseries 南京大学} }
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    \cs_set_protected:Npn \__nju_logo_name:Nn #1#2 { { \zihao{1} \bfseries 南京大学 } }
  }
\ExplSyntaxOff

\begin{document}

\maketitle

\frontmatter

\begin{abstract}
  本文研究离散信源的熵。摘要应概括研究的问题、方法、结果和结论。
\end{abstract}

\begin{abstract*}
  What the problem was, what you did, what you found, and why it matters, in a few short
  paragraphs. Most examiners read the abstract and the conclusions first.
\end{abstract*}

\tableofcontents
\listoffigures
\listoftables

\mainmatter

\chapter{引言}
\label{chap:introduction}

本章说明论文研究的问题及其意义。信息论的基本概念见文献~\cite{shannon1948}。
This chapter states the problem and the plan of the thesis.

\section{研究内容}

列出本文要回答的两到三个问题。

\chapter{方法}
\label{chap:method}

\section{模型}

设离散信源有 $n$ 个符号，其概率为 $p_1, \dots, p_n$，则信源的熵为
\begin{equation}
  H = -\sum_{i=1}^{n} p_i \log_2 p_i ,
  \label{eq:entropy}
\end{equation}
当各符号等概率时熵最大。

\section{数据}

表~\ref{tab:data} 列出了实验所用的三个数据集。

\begin{table}[htbp]
  \centering
  \caption{实验数据集}
  \label{tab:data}
  \begin{tabular}{lrr}
    \hline
    数据集 & 样本数 & 符号数 \\
    \hline
    A & 1200 & 4 \\
    B & 3500 & 8 \\
    C & 9800 & 16 \\
    \hline
  \end{tabular}
\end{table}

\chapter{结果与结论}
\label{chap:results}

图~\ref{fig:entropy} 给出二元信源的熵随概率 $p$ 的变化，在 $p = 0.5$ 时取最大值 1 比特，与式~(\ref{eq:entropy}) 一致。

\begin{figure}[htbp]
  \centering
  \begin{tikzpicture}[x=6cm,y=3cm]
    \draw[->] (0,0) -- (1.1,0) node[right] {$p$};
    \draw[->] (0,0) -- (0,1.15) node[above] {$H(p)$};
    \foreach \t in {0.5,1} \draw (\t,0) -- (\t,-0.03) node[below] {\t};
    \draw[thick,domain=0.01:0.99,samples=60] plot (\x, {-\x*log2(\x)-(1-\x)*log2(1-\x)});
  \end{tikzpicture}
  \caption{二元信源的熵}
  \label{fig:entropy}
\end{figure}

\printbibliography

\backmatter

\begin{acknowledgement}
  感谢导师的悉心指导，感谢所有给予帮助的老师和同学。
\end{acknowledgement}

\end{document}

@article{shannon1948,
  author  = {Shannon, C. E.},
  title   = {A Mathematical Theory of Communication},
  journal = {Bell System Technical Journal},
  volume  = {27},
  number  = {3},
  pages   = {379--423},
  year    = {1948},
  doi     = {10.1002/j.1538-7305.1948.tb01338.x}
}

% Add your own entries here, then cite them with cite{key}.