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A New Top-Down Context-Free Parsing for Syntactic Pattern Recognition

机译:句法模式识别的新自制上下背景解析

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The numerous different mathematical methods used to solve pattern recognition snags may be assembled into two universal approaches: the decision-theoretic approach and the syntactic (structural) approach. In this paper, at first syntactic pattern recognition method and formal grammars are described and then has been investigated one of the techniques in syntactic pattern recognition called top -down tabular parser known as Earley's algorithm Earley's tabular parser is one of the methods of context -free grammar parsing for syntactic pattern recognition. Earley's algorithm uses array data structure for implementing, which is the main problem and for this reason takes a lots of time, searching in array and grammar parsing, and wasting lots of memory. In order to solve these problems and most important, the cubic time complexity, in this article, a new algorithm has been introduced, which reduces wasting the memory to zero, with using linked list data structure. Also, with the changes in the implementation and performance of the algorithm, cubic time complexity has transformed into O (n*R) order.
机译:用于解决模式识别断枝的许多不同的数学方法可以被组装成两个通用的方法:决策理论方法和句法(结构)的方法。在本文中,在第一句法模式识别方法和形式文法描述,然后已被研究的在句法模式识别技术所谓的顶部一个-down片状解析器称为厄雷算法厄雷的片状解析器的上下文-free的方法之一语法分析句法模式识别。厄雷的算法使用数组实现,这是主要的问题,为此需要花费大量的时间,搜索在阵列和语法分析,并浪费了大量的内存。为了解决这些问题,最重要的是,三次时间复杂度,在这篇文章中,一种新的算法已被引入,从而减少浪费内存为零,使用链表数据结构。另外,在实施和算法的性能的变化,立方时间复杂性转化为为O(n * R)顺序。

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