查询词典 algorithm of division

This article proposed one kind of improvement algorithm in this foundation, this algorithm has defined a filter balance factor formula, according to this formula, we readjustment filter balance factor value appropriately, through controlsling the LMS filter coefficient's freezing and the restoration, we solute echo puzzle perfectly; In the telephone condition examination algorithm aspect, in view of the busy signal examination algorithm which has has only been able to examine the busy signal, but cannot examine the dial tone, hang the staccato the deficiency, this article improves its algorithm to enable it to apply these aspects, make it can be better used in the actual system application.

本文在此基础上提出了一种改进算法，该算法定义了一个滤波器平衡因子的计算公式，根据此公式，适当调整滤波器平衡因子的阀值，通过控制LMS滤波器系数的冻结和恢复，很好的解决了回声的困扰；在话机状态检测算法方面，本文针对已有的忙音检测算法只能检测忙音，而不能检测拨号音、挂断音的不足之处，研究改进其算法使之能够应用到这些方面，更好的为实际系统的应用服务。

First, the character clustering algorithm regards the character as our features and then it can cluster these sentences of our target words to the correct group without any other resources. The average precision is 66.1%. Second, in the concept clustering algorithm of the aggregate computing, we use HowNet as the knowledge base of our feature words and obtain the concepts of these words. We cluster the sentences which have the same or similar concepts of the feature words into the same group. And then we can complement some lacks of the character clustering algorithm. The average precision is 72.3%. Third, regarding the concept clustering algorithm of the sememe distance, we use the sememe distance to compute its concept similarity. It improved similarity measure of the concept clustering algorithm of the aggregate computing. It achieves 81% average precision and gets better cluster quality.

词形分群演算法不受语料资源限制，能将词形相似且词义相近的词汇所属的句子分到同一群，经过人工验证，得到了66.1%的平均正确率；基於集合计算的概念分群演算法使用了知网做为撷取特徵词汇的知识库，透过知网取得词汇的概念，将具相同或相似概念的特徵词汇所属的句子分成同一群，补足词形分群演算法的不足，得到72.3%的平均正确率；基於义原距离的概念分群演算法则利用义原间的距离计算特徵概念的相似度，进一步改善了基於集合计算的概念分群演算法在相似度衡量的问题，得到81%的平均正确率，达到更好的分群效果。

Three methods to build soft-sensor model of Radial Basis Function neural network (K-means clustering algorithm, mixed Genetic Algorithm, mixed hierarchical Genetic Algorithm) is investigated and verified in simulation.In the condition of setting hidden layer's node numbers, K-means clustering algorithm and mixed Genetic Algorithm can satisfy online prediction of component content.

研究了三种建立RBF网络软测量模型方法(K-均值聚类算法、混合遗传算法、混合递阶遗传算法)，并进行仿真试验验证。K-均值聚类算法与混合遗传算法在预先设定隐含层节点数的情况下能满足组分含量在线估计。

Firstly, on the basis of defining the characteristics of project and reviewing the mathematical models for RCPSP, we constructed the mathematical model for RCPSP under the condition that there is non-fixed duration and splittable tasks in project; In order to solve above model, we emphatically discussed the basic principle of the swarm intelligence algorithm--the particle swarm optimization algorithm as well as improvement research for current algorithm, and then proposed a new improved particle swarm optimization algorithm and analyzed its application process in the resource-constrained project scheduling problem; Lastly, in order to confirm the validity of the model and the algorithm, we took an experiment based on 108 instances that produced by problem instance generator which was developed by our team.

首先，在对RCPSP项目特征进行界定以及对项目进度优化模型回顾的基础之上，构建了基于活动工期不固定、任务可拆分特征的RCPSP的数学模型；为了求解上述模型，本文详细阐述粒子群优化算法(Particle Swarm Optimization，PSO)的基本原理以及当前对其改进的研究成果，提出了一种新的改进PSO算法，并对其在RCPSP的应用过程进行了设计；最后，为了检验模型的有效性及算法的优越性，基于梯队内部开发的案例生成器生成的108个算例，进行了仿真试验。

Researches on kernel clustering algorithms. After combining K-means clustering algorithm and the theory of kernel-based learning algorithms, we propose a fast kernel K-means clustering method which is based on CPD kernel. The experiment results indicate that the clustering effect of the algorithm is better than that of K-means algorithm, the clustering speed of the algorithm is also fast than that of K-means algorithm.

核聚类算法的研究：探讨了K-均值聚类算法，通过将核学习理论与K-均值聚类算法结合，提出了一种基于CPD核函数的快速核K-均值聚类算法，并将该算法与基于Mercer核的核聚类算法进行了比较，实验结果显示，我们的方法不仅比K-均值聚类算法的聚类效果好，而且聚类速度快。

Image segmentation, to achieve the classic division algorithm, and the use of group Algorithm the division results.

在图像分割部分，实现了经典的分合算法，并且使用成组算法改进了分合的效果。

This paper discusses some algorithm of division and square root. Inmy design, I use improved Newton algorithm for square root and Goldschmidt al-gorithm for division.

本文探讨了当前使用较多的一些浮点除法/开方算法，并在设计中采用了改进的牛顿迭代来计算开方、使用 Goldschmidt 算法来实现除法。

On object division algorithm based on 3D information: the algorithms for object surface division are studied and a new algorithm is presented.

关于目标物体分割算法：讨论了利用框架特征的目标物体表面分割算法，提出了一种基于立体信息的目标物体表面分割算法。

A structure of space-time diversity virtual double-route weighting interference mitigating is proposed, and the corresponding practical algorithm is derived in detail using block matrix inversion formula and matrix inversion theory for mitigating interference signals from both other cells and other users of local cell in the DS-CDMA up-link communication case. Performances of such algorithm are thoroughly analyzed through simulation and analytical results. The up-link and down-link channel characters and their relationship of DS-CDMA communication system are thoroughly analyzed, and the relationship of space-time diversity weighting matrix between time division duplexing and frequency division duplexing these two different transmission ways is derived.

本论文深入地比较了DS-CDMA通信系统的上传情形与下传情形的信道特性及其它们相互之间的关系；深入地分析并得到了时分双工和频分双工两种不同的传输模式下的上传情形与下传情形的空时分集权系数矩阵之间的数量关系，从而使得能够利用在基站端所拥有的上传情形的空时分集接收权系数矩阵信息以及其他信息在基站端直接形成空时分集发射权系数矩阵；推导了下传情形移动用户接收机端的最优组合接收策略及其算法；进一步地，对时分双工传输模式下的下传情形的通信系统性能和频分双工传输模式下的下传情形的通信系统性能进行了深入的比较仿真研究。

And it comparatives and analyses the efficiency of three algorithm's cliping through an example, the example proved: Liang－Barsky algorithm efficiency is highest, Cohen-Sutherland next best, and the midpoint of division algorithm efficiency is lowest.

并通过一个实例对三种算法的裁剪效率比较分析，实例证明：梁友栋一Barsky算法效率最高，Cohen—Sutherland次之，而中点分割算法裁剪效率最低。

"Please accept this talisman as a token of our thanks."

请收下这个护身符以表达我们的感谢。

If I have that magic, I will be more acceptable in the society.

如果我拥有那种魔法，我将更加被这个社会所容纳。