在算法上

Finally, FastICA in time domain is derived based on instantaneous BSS system, and convolutional mixture BSS algorithm in frequency domain is obtained based on convolutional mixture BSS in time domain. Then we combine the two algorithms together and present the complex-value FastICA algorithm in frequency domain, which is a new BSS technique. We merge preprocessing in time domain and correlation coefficient solution in time domain into this new algorithm and present Time-Frequency domain FastICA BSS System.

最后，本文在瞬时混合盲分离系统基础上推出时域FastICA算法，在时域卷积混合盲分离系统基础上推出频域卷积混合盲分离算法，将这两种算法相结合，提出了频域复值FastICA算法，再将此算法与时域预处理方法以及最后回到时域中的利用相关系数求解分离信号方法相结合，从而建立了基于FastICA的时频域盲分离系统，并将其应用到实际环境中的语音信号盲分离中。

In this paper, we introduce the algorithm of Schoof-Elkies-Atkin to compute the order of elliptic curves over finite fields. We give out a fast algorithm to compute the division polynomial f〓 and a primitive point of order 2〓. This paper also gives an improved algorithm in computing elliptic curve scalar multiplication. Using the method of complex multiplication, we find good elliptic curves for use in cryptosystems, and implemented ElGamal public-key scheme based on elliptic curves. As a co-product, we also realized the algorithm to determine primes using Goldwasser-Kilian's theorem. Lastly, the elliptic curve method of integer factorization is discussed. By making some improvement and through properly selected parameters, we successfully factored an integer of 55 digits, which is the product of two 28-digit primes.

本文介绍了计算有限域上椭圆曲线群的阶的Schoof-Elkies-Atkin算法，在具体处理算法过程中，我们给出了计算除多项式f〓的快速算法和寻找2〓阶本原点的快速算法；标量乘法是有关椭圆曲线算法中的最基本运算，本文对[Koe96]中的椭圆曲线标量乘法作了改进，提高了其运算速度；椭圆曲线的参数的选择直接影向到椭圆曲线密码体的安全性，文中利用复乘方法构造了具有良好密码特性的椭圆曲线，并实现了椭圆曲线上ElGamal公钥体制；文中还给出了利用Goldwasser-Kilian定理和椭圆曲线的复乘方法进行素数的确定判别算法；最后讨论了利用椭圆曲线分解整数的方法并进行了某些改进，在PC机上分解了两个28位素数之积的55位整数。

It solves the problem that the unitary contour presentation can not correctly extract face contour in a face image which suffers from scale, rotation etc. The definition of the internal and external energy function is provided. At the same time, the global matching algorithm and local matching algorithm is given. The experiment shows that this presentation and the accompanying matching algorithm can be used to extract the face contour very well. So the image segmentation can be implemented by using it.②By analyzing the recognition principle of PCA method, we can conclude that the face images coming from different surrounding consist of different face image space. This is the essential reason that makes the generality of PCA method worse. Also, we give a measurement means to measure the distance from different face image space, so we can analyze face image space more conveniently.③We also construct various scale models and rotation pose models to detect the scale and rotating angle of face image to be recognized. The experiment results show that the detecting precision is very high. So it is good for face image feature extraction and face image representation.④Similarly, we construct local feature models of face image and utilize them to detect the local feature of face image. At the same time, we put forward a novel face image local feature detection algorithm, locating step by step. The experiment results show that this method can accurately detect the location of local face feature in a image.⑤A novel face image presentation model, dual attribute graph , is put forward. Firstly, it utilizes attribute graph to present the face image, then exact the local principal component coefficient and Gabor transform coefficient of thc pixels which corresponds to the nodes of the graph as the attribute of the nodes. This representation fully makes use of the statistical characteristic of the local face feature and utilizes Gabor transform to present the topographical structure of face image. So DAG has more general property.⑥Based on the DAG presentation, we give a DAG matching function and matching algorithm. During the design of the function and algorithm, the noise factor, e. g., lighting, scale and rotation pose are considered and tried to be eliminated. So the algorithm can give more general property.⑦A general face image recognition system is implemented. The experiment show the system can get better recognition performance under the noise surrounding of lighting, scale and rotation pose.

本文在上述研究的基础上，取得了如下主要研究成果：①构造了一个通用的人脸轮廓模型表示，解决了由于人脸图象尺度、旋转等因素而使得仅用单一轮廓表示无法正确提取人脸轮廓的问题，并给出了模型内、外能函数的定义，同时给出了模型的全局与局部匹配算法，实验表明，使用这种表示形式以及匹配算法，能够较好地提取人脸图象的轮廓，可实际用于人脸图象的分割；②深入分析了PCA方法的识别机制，得出不同成象条件下的人脸图象构成不同的人脸图象空间的结论，同时指出这也是造成PCA方法通用性较差的本质原因，并给出了不同人脸空间距离的一种度量方法，使用该度量方法能够直观地对人脸图象空间进行分析；③构造了各种尺度模板、旋转姿势模板以用于探测待识人脸图象的尺度、旋转角度，实验结果表明，探测精确度很高，从而有利于人脸图象特征提取，以及图象的有效表示；④构造了人脸图象的各局部特征模板，用于人脸图象局部特征的探测；同时提出了一种新的人脸图象局部特征探测法---逐步求精定位法，实验结果表明，使用这种方法能够精确地得到人脸图象各局部特征的位置；⑤提出了一种新的人脸图象表示法---双属性图表示法；利用属性图来表示人脸图象，并提取图节点对应图象位置的局部主成分特征系数以及Gabor变换系数作为图节点的属性，这种表示方法充分利用了人脸图象的局部特征的统计特性，并且使用Gabor变换来反映人脸图象的拓扑结构，从而使得双属性图表示法具有较强的通用性；⑥在双属性图表示的基础上，给出双属性图匹配函数及匹配算法，在函数及算法设计过程中，考虑并解决了光照、尺度、旋转姿势变化等因素对人脸图象识别的影响，使得匹配算法具有较强的通用性；⑦设计并实现了一个通用的人脸图象识别系统，实验结果表明，该系统在图象光照、尺度、旋转姿势情况下，得到了较好的识别效果。

The study establishes the compression of models and algorithms for vector graphics data on different basis, including on the basis of vector graphic factors of B spline curves in predecessors research; on the basis of rectangle graphic factors in main axis mode; on the basis of the application of Hough transform to polygonal line, ellipse and circle, so the study improves the models and algorithms of compression for vector graphic data.The compression for vector graphic data mainly studies the data of storing graphic factors.

本文研究的内容是：根据对以往各种曲线矢量数据压缩模型与算法的研究，建立了基于B样条的曲线矢量图形要素的数据压缩模型和算法；在前人研究的基础上，建立基于主轴模式的矩形图形要素的数据压缩模型和算法；本文作者将Hough变换应用到折线、圆及椭圆图形要素的矢量数据压缩上，在此基础上改进了基于Hough变换的折线、圆及椭圆图形要素的数据压缩模型和算法。

This paper first analyses and summarizes the ststus quo and evolution trend of encryption, some common used cryptograph are introduced, including the algorithms used in symmetric cryptosystem and asymmetirc cryptosystem. We describe the theory of each algorithms and compare the elliptic curve cryptosystem with the other two asymmetric cryptosystems to show the advantages of this algorithm. Second, the principle of ECC is discussed, including the math foundation of ECC, basic conception of elliptic curves, constructiong idea of ECC, operation on the elliptic curve and so on. Third, the current attacks of ECC were analyzed deeply, and an algorithm based on limited prime number field was constructed. We analyzed its realizability in theory, and implement it by using certain function of MIRACL software package. Latter half in this paper, the implementation model of a simple elliptic curve encryption system which based on GF has been introduced. The paper also put a deep analysis on the algorithm of point addition and point multiplication.

本文首先对密码技术的发展现状及其发展趋势进行了分析和综述，详细的介绍了私钥密码系统和公钥密码系统的发展，说明各种算法的原理和优缺点，并给出了一些典型的密码体制的简要分析，重点将椭圆曲线算法与其它几种公钥密码算法比较，说明椭圆曲线算法的优势；其次，探讨了椭圆曲线密码体制的原理，包括椭圆曲线密码的数学基础、基本概念、椭圆曲线密码体制的构造思想等问题；第三作者对椭圆曲线的攻击现状作了详细的分析，针对所使用的大素数域F_p，设计了素数域上安全椭圆曲线产生的算法，从理论上做了可实施性分析，从软件上做了具体实现；在本文的后半部分，提出了一个简单的基于有限素数域上的椭圆曲线加密方按算实现模型，并对SECES中设计的点加和点乘运算进行了深入分析。

On global optimal algorithms, a heuristic 0-1 Integer Liner Programming algorithm is achieved, which combines heuristic enumeration method and revised simplex method. Simulation experiments show that the degree and optimization efficiency in our algorithm is obviously improved compared with the MATLAB 7 bintprog function that is a 0-1 integer programming algorithm. Moreover our algorithm isn\'t relevant to the scale changes of Web services composition and candidate service sets, thus it is applicable for the scenes that the scales of Web services composition changed dynamically. But for Web services composition with service alliance, the algorithm is unable because the non-linear global optimal model of the fitness function and QoS constraints can\'t be expressed in linear mode.

在全局优化算法研究上，基于启发式0-1整线性规划算法结合了修正单纯形法和启发式枚举法，仿真实验表明该算法与MATLAB 7的0-1整数规划方法比较，在优化程度及优化效率上得到了显著改进，并且对服务组合和候选服务集合的规模变化没有明显的相关性，因而该算法可用于服务组合规模动态变化的场景，但该算法不能应用于存在服务联盟的非线性全局优化模型。

Firstly, the paper expatiates the essence principle of the motion estimation based block matching, introduces Full Search method and several typical motion estimation fast algorithms, and analyzes each characteristic, then to sum up the key technology for increasing the motion estimation search efficiency; Secondly, it stress introduces three motion estimation fast improved algorithms: the improved algorithm based Full Search method, it imports successive elimination algorithm、subsample and termination condition to increase search speed for enhancing the real time of Full Search.

本文首先阐述了基于块匹配法的运动估计基本原理，介绍了全搜索法和几种典型的运动估计快速算法，分析了各算法的特点，在此基础上总结了提高运动估计搜索效率的几个关键技术。接着重点介绍了本文提出的三种运动估计快速改进算法。基于全搜索的改进算法，是在全搜索的基础上尝试引入了连续排除算法、子抽样和终止条件来提高搜索速度，增强全搜索的实时性。

A Multi-Species Cooperative PSO algorithm is developed using the ideas of species dividing in the bionomical world. The algorithm is shown to have guaranteed convergence to the global optimum. Furthermore, the training strategies of RBF network structures and weights based on the MCPSO aigorithm is proposed. Simulation results show that the algorithm is effective in such fields as chaotic time-sequence forecasting, system identification, speech signal processing and etc.

在分析基本微粒群算法和协同微粒群算法特点的基础上，借鉴生态学中的种群划分思想，设计出一种多种群协同进化微粒群算法，并分析了该算法的收敛性能；在分析径向基函数神经网络结构的基础上，提出了基于多种群协同进化微粒群算法的径向基函数神经网络结构和权值优化设计策略，并在混沌序列预测、系统辨识、语音信号处理等应用仿真实验中验证了算法的有效性。

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。

Moreover, A hybrid algorithm, ALHybrid, which is made of the algorithm LIDBSO and the algorithm AprioriIpv, is designed. Two algorithm, MQC_Apriori and MQC_LIDBSO, are given to mining multiple level quantitative association rules with item constrains. Two algorithm, PMARⅡ and PMARⅢ, which are based on different sequential mining algorithms, are given for parallelling mining association rules. In order to solve the mining association rules problem when we add a set of data to a database or delete a set of data from a database, two incremental updating algorithm, EUAR and EUAR, are given. Three incremental updating algorithm for association rules mining, DIUAⅠ, DIUAⅡ and DIUAⅢ, are dedigned to solve the three kinds of association rules incremental updating problem in distributed databases.

另外，文中还设计了一个算法LIDBSO与算法AprioriIpv相结合的混合采掘算法ALHybrid；对于多层次、带约束、多值属性关联规则的采掘问题，给出了两个采掘算法：算法MQC_Apriori和算法MQC_LIDBSO；在关联规则的并行采掘方面，还设计了两个基于不同顺序关联规则采掘算法的并行算法：算法PMARⅡ和算法PMARⅢ；在关联规则的增量式更新问题上，还给出了两个改进算法：算法EUAR和算法EUARˉ，分别用于解决当数据库增加或删除一个数据集合时的关联规则增量式更新问题；针对分布式数据库中的关联规则增量式更新的三类问题，提出了三个增量式更新算法：算法DIUA Ⅰ、算法DIUAⅡ和算法DIUAⅢ。

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。