算法的

The topics are divided into three parts: the first part introduced the basic concepts of algorithms, mathematical algorithms and algorithms based on complexity analysis scheduling problem for the second part of the problem and plans to discuss a variety of existing algorithms, and describes the design of commonly used algorithms including sub-rule law, greedy method, dynamic programming, backtracking and branch and bound method, and describes the complexity of the calculation, as well as NP-complete problem the third part of the model on parallel computing and parallel algorithm design techniques.

全书分为3个部分：第一部分介绍算法的基本概念、算法的数学基础以及算法复杂度分析；第二部分针对排序问题和图的问题，讨论各种已有的算法，并介绍常用的算法设计方法包括分治法、贪心法、动态规划法、回溯法和分支限界法，并介绍了计算的复杂性以及NP完全问题；第三部分讲述并行计算模型和并行算法设计技术。

In chapter 2 we propose a linear equality constraint optimization question , the new algorithm is combined with the new conjugate gradient method(HS-DY conjugate gradient method)and Rosen"s gradient projection method , and has proven it"s convergence under the Wolfe line search.In chapter 3 we have combined a descent algorithm of constraint question with Rosen"s gradient projection, and proposed a linear equality constraint optimization question"s new algorithm, and proposed a combining algorithm about this algorithm, then we have proven their convergence under the Wolfe line search, and has performed the numerical experimentation.

在第三章中我们将无约束问题的一类下降算法与Rosen投影梯度法相结合，将其推广到线性等式约束最优化问题，提出了线性等式约束最优化问题的一类投影下降算法，并提出了基于这类算法的混合算法，在Wolfe线搜索下证明了这两类算法的收敛性，并通过数值试验验证了算法的有效性。

The results show that the two kinds of basic ant colony algorithm have better performance than classical K-means algorithm and hierarchal clustering algorithm, the two kinds of extended algorithm have better performance than corresponding basic ant colony algorithm.

实验结果表明，两种基本蚁群算法的聚类效果优于经典的K_means算法和层次聚类算法；两种改进的算法又分别优于相应的基本蚁群算法，达到了算法改进的目的。

The new algorithm effectively combines the advantages of ACO and PSO. It adopts the grid method for environment modeling and makes use of the efficiency and succinctness of PSO to obtain the initial distribution of pheromone, reducing the number of iterations and accelerating the convergence. At the same time, by using the parallelizability of ants and distributed parallelized-searching technology, the performance of the algorithm is effectively improved.

该方法有效地结合了粒子群算法和蚁群算法的优点，采用栅格法进行环境建模，利用粒子群算法的快速简洁等特点得到蚁群算法初始信息素分布，以减少迭代次数，加快算法的收敛速度；同时利用蚁群算法之间的可并行性，采用分布式技术实现蚂蚁之间的并行搜索，求解精度高等优点，求精确解。

First,we proposes the acceleration of Monte Carlo EM Algorithm,which is based on Monte Carlo EM Algorithm and Newton-Raphson algorithm,to improve the convergence rate;Second,the it is shown that the accelerated EM algorithm we proposed has quadratic convergence rate in a neighborhood of the posterior mode;Finally,its excellent performance in convergence rate is illustrated by a classical example.

受Monte Carlo EM算法与EM加速算法启发，本文构造了一种新的EM算法，称为Monte Carlo EM加速算法；证明了该算法在似然函数/后验分布的众数的附近确实具有二次收敛速度，改进了Monte Carlo EM算法的收敛速度；并通过一个数值例子的计算结果说明了该算法的优良性，它兼具实现简单及收敛速度快的特点。

this text briefly introduce association rule.by analyzing the application of classic apriori algorithm, apriori algorithm is found that it has some disadvantages. and then farm_new algorithm and the apriori algorithm of riddling compression those improving the association rule algorithm are proposed.

简要地介绍了关联规则，通过对关联分析的经典算法-apriori算法的分析，发现了经典算法apriori算法的缺陷，给出了改进的关联规则算法farm_new算法和基于筛选压缩的apriori挖掘算。

Considering the difference of the use of clustering algorithms caused by the diffference of data distribution, on the base of the analysis of Kmeans algorithm, fuzzy Cmeans algorithm and genetic algorithm, a new algorithm was brought forward based on the genetic algorithm and the improved neighbor function criterion. In view of the intrinsic connection of the special and the advantage of genetic algorithms wholesearch strategy, to a certian extent, this new algorithm solve the problem about the uncompact and irregular data distribution.

考虑到空间数据分布特性差异造成聚类算法采用的不同，在比较分析K均值算法、模糊均值算法和遗传算法的基础上，提出了改进的近邻函数准则，并有机整合形成遗传算法与改进近邻函数准则的新算法，综合了遗传算法的全局性概率搜索的优点，并考虑到空间数据内在的连接方式，在一定程度上较好地解决了数据的非致密非规则分布问题。

When the number of high accuracy guide stars identified is large, the QUEST algorithm has obvious superiority.According to night-sky observation, based on the guide star flag and the star- Identification information, the selection principle of attitude determination algorithm are given.

四姿态确定算法进行了改进的TRIAD算法和QUEST算法的探讨，这两种定姿算法各有千秋，在识别出的高精度导航星只有2颗的情况下，QUEST算法无法给出姿态，而改进的TRIAD算法可以进行三轴姿态的反演；但在识别出的高精度导航星多的条件下QUEST算法有明显的优势。

The method of obtaining time delay parameters with the reverse access channel is discussed. The modified algorithms of classic correlation methods of TOA estimation are proposed. Noncoherently combining algorithm and group coherent combining algorithm are given. They decrease the computational complexity and are more suitable for implementations in practical systems. The leading edge detection algorithm is proposed to mitigate the effect of multipath in TOA estimation. Then the secondary search method is proposed, it can solve the matching issue of PN code in CDMA systems. The location algorithms based on LS are discussed; include circular trilateration with LS, hyperbolic trilateration with reference differencing, hyperbolic trilateration with sequential differencing and circular trilateration with TOA differences. The design and implementation of wireless location system based on TOA/TDOA in CDMA2000 systems are given. The location process is discussed, and the hardware and software implementation of TOA estimation are given. Finally, the wireless location system which uses TOA estimation and LS location algorithms above is tested in the real environment.

文中讨论了采用CDMA2000反向链路中的接入信道来获取时延的方法和过程；对TOA估计的传统的相关法进行了改进，提出了非相干合并相关法和分组合并相关法，减少了基于相关的时延估计算法的运算量，提高了算法的实用性，对算法进行了仿真和性能分析；采用边缘检测技术有效减少了TOA参数估计中的多径干扰，提高了时延参数估计的准确度；提出了一种TOA估计的二次搜索法，解决了多个定位测量单元同时进行TOA估计的PN码匹配问题，进一步了提高TOA估计的精度；在采用时延值的定位算法中引入了基于LS的圆周法、基于参考差的双曲线法、基于相邻差的双曲线法和基于TDOA的圆周法，讨论了各算法的应用条件，进行了算法性能的仿真分析；给出了CDMA2000系统中的TOA/TDOA的无线定位的系统方案和实现流程，并对TOA值估计算法进行了软硬件实现，还对采用TOA估计算法、LS定位算法和定位系统设计方案实现的定位系统的进行了现场定位性能测试。

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。

The split between the two groups can hardly be papered over.

这两个团体间的分歧难以掩饰。

This approach not only encourages a greater number of responses, but minimizes the likelihood of stale groupthink.

这种做法不仅鼓励了更多的反应，而且减少跟风的可能性。