In this paper we introduce two phases modeling and fuzzy profile tree pattern matching method.
针对这种现象，文中提出了一种两阶段模式建立方法和基于模糊轮廓树的模式匹配方法。
This approach is implemented by rule set building, tree pattern matching and math expression transformation.
该方法通过建立数学规则库，对两个数学表达式进行树型模式匹配和算式变换来实现。
This method is easier than tree pattern matching, and can be used in other DSP processors supporting parallel instructions.
这种方法比树模式匹配方法更容易实现，并适用于支持并行指令的其他DSP处理器。
Its execution mechanism is pattern matching. The paper focuses the discussion on the improvement to bottom-up tree pattern matching. Our system has quick response time and strong descriptive power.
本文介绍该语言的一个实现系统，该系统是以方程逻辑为语义基础，模式匹配为执行机制，本文讨论了自底向上模式匹配方法及其改进，整个系统具有时间响应快、描述能力强的特点。
While XPath provides a compact and elegant way of traversing an XML tree, its pattern matching functions have a rather limited capability.
尽管XPath提供了一种紧凑和优雅的方式来遍历xml树，但其模式匹配函数的能力相当有限。
Regular expressions provide much richer pattern matching across strings of text, but are as easy to use as XPath when traversing a data structure such as an XML tree.
正则表达式提供了跨文本的字符串的更丰富的模式匹配，但在遍历诸如xml树这样的数据结构时，它和XPath一样易于使用。
It is not hard to integrate a pattern-matching library with the tree visitor to get to a point where visitors can leverage tree patterns.
您可以轻松集成模式匹配库与树访问者，使访问者能够利用树模型。
In this paper, binary tree structure substitutes for linked list structure used in traditional IDS, aiming to better storage of rules and improve pattern matching so as to speed intrusion detection.
提出以二叉树结构取代原有入侵检测系统采用的链表结构，旨在改进入侵规则的存储和模式匹配，提高检测速度。
Randomized tree is a supervised classification algorithm for pattern recognition, which can be effectively used in augmented reality feature recognition and matching.
随机树分类算法是一种有监督学习的模式识别分类算法，可有效地应用于增强现实系统中的特征识别与匹配。
Randomized tree is a supervised classification algorithm for pattern recognition, which can be effectively used in augmented reality feature recognition and matching.
随机树分类算法是一种有监督学习的模式识别分类算法，可有效地应用于增强现实系统中的特征识别与匹配。
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