自然语言中的”语言“:规则的组合
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<img src="data:image/png;base64,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" 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" width="40px" /> 1 关键字/保留字 const
int
2 标记符 WhatIsYourName
AnyNumber
3 常量 “123"
4 分割符号 ()
5 操作符号 +
*
⇒表达式⇒语句⇒函数⇒程序
</aside>
形式语言中的“语言”:一个集合【by Chomsky】
<aside> 🚧 1 字母表 $\Sigma$:任意字符(非空性$\Sigma\ne\emptyset$,有穷性,单一性-可区分,不重复) 2 字符串:字母表的任意排列、重复,$\varepsilon$ 为空串 3 语言$L$:任意多个字符串的集合,如$\{\varepsilon\},\empty$,$(\Sigma,L\subseteq \Sigma^)$ 3-1 句子$x$- $x$$\Sigma,\forall L\subseteq \Sigma^,\forall x\in L$
</aside>
既然语言是集合,那么它也可以定义运算。
连接运算:
引入闭包
的概念(方便描述连接后的形式)
克林闭包:A中所有元素的任意次连接构成的集合
$$ A^*=\bigcup_{i=0}^{\infty}A^i. $$
正闭包:
$$ A^+=\bigcup_{i=1}^{\infty}A^i,\\A^*=A^+\bigcup\{\varepsilon\} $$
这样使用闭包的概念,可以标识字母表的所有表示(类似于$\text{span}$的功能)
语言可以从两方面定义,可以证明这两种方法是等价的。
$\textcircled{1}$产生语言:基本句子+句子形成规则(语法规则)↔形式语言;
产生式:$S$ start 符合语言的串;$\to$ 定义为,是,替代为; 推导过程:右边代替左边,$S$等为非终结符,可以递归替换。
定义式:
$$ \left\{\begin{matrix} I\to L\ \ \ \\ I\to LS\\ S\to SS|L|D \end{matrix}\right. $$
$\textcircled{2}$接受语言:模式接受,所有能接受的串构成语言↔自动机;