正项级数敛散性的一个判别法

基于正项级数的比较判别法和p-级数的敛散性,给出一个与D’Alembert判别法和Cauchy判别法平行的判别正项级数敛散性的方法.并通过实例对所给判别法的可行性进行检验,发现它是已有方法的一个有效补充.     

正项级数Kummer判别法的一个推广及其应用

本文给出并证明了正项级数 Kum mer判别法的一个推广 ,在更一般的意义下讨论了通常的正项级数判别法 ,扩大了原来的判别法判断敛散性的范围 .     

正项级数收敛性的一种新的判别法

将正项级数收敛性的 D′Alembert比值判别法和 Cauchy根值判法的数学思想融合到一起 ,利用正项级数的比较判别法和级数的某些基本性质 ,给出了正项级数收敛性的一种新的判别法 ,暂时称之为 Z-判别法 .     

正项级数的D—C判别法

本将正项级数的比值审敛法（达朗贝尔D'Alembert判别法）和根值审敛法（柯西Cauchy判别法）结合起来，得到正项级数的一个新的审敛法，且称之为D－C判别法。     

数列的几乎单调性

讨论了数列的几乎单调概念,利用数列的几乎单调性,得到了相应条件下的莱布尼茨判别法、阿贝尔判别法和狄利克雷判别法．     

Cauchy判别法的推广

以正项级数的比较判别法为基础,得到判别正项级数敛散性的两个判别方法,它可以作为Cauchy判别法对正项级数∑u_n,(u_n0),ρ=(?)u_n~(n/1)当ρ=1失效时的一个补充,把它称为Cauchy判别法的推广.     

正项级数的Raabe对数判别法

在正项级数敛散性Raabe判别法和第一对数判别法的基础上,以P-级数作为比较标准,讨论了第二对数判别法,并且证明了Raabe判别法和第二对数判别法的等价性.     

p-达朗贝尔判别法及其应用

对正项级数的达朗贝尔判别法作了推广,提出并证明了p-达朗贝尔判别法,扩大了其使用范围.进一步利用数列和子列的收敛关系,证明了其与柯西判别法之间的关系.最后通过例子对p-达朗贝尔判别法进行了验证.     

无穷级数中高斯判别法的进一步讨论

经过计算和逻辑推理,提出两种判别范围较大的正项级数判敛法,即广义高斯判别法及广义拟对数判别法,并对这两个判别法进行了比较.     

关于正项级数收敛性

本在Cauchy判别法和D’Alembert判别法基础上，对正项级数的收敛性提出了一个新的判别方法。     

Bayes判别分析在医疗数据处理中的应用

本文利用判别分析的基本原理和方法,针对肝硬化医疗数据建立数学模型,然后利用SPSS16.0作为工具求解模型,得到了三个有意义的能判别归类的函数判别式。     

基于R软件的Bayes判别分析在医学中的应用

Bayes判别在进行判别分析时考虑到各总体出现的先验概率、预报的先验概率及错判造成的损失,其判别效能优于其他判别方法.对Bayes判别方法详细介绍的基础上,利用R软件对一组舒张压和胆固醇数据分别进行Bayes判别分析、Fisher判别分析和基于距离的判别分析,对比三种不同方法下得到的判别结果,结果表明Bayes判别分析得到的分类结果精度较高,Bayes判别分析在医学领域有较好的应用前景.     

有序判别分析新算法及其应用

判别分析是用已知分类数据建模对未知分类数据进行判别的方法,所用数据和分类不分顺序。要对有序又有周期数据进行判别分析,就要探索有序判别的新方法。这种方法的分类应当是有序的,并且能够排除事物发展周期性的干扰。本文介绍多元数据有序判别分析新方法的原理、建模流程、应用流程和应用实例。这种判别分析将分类建模与判别归类分开。新方法对多元数据建模时在多类模型中建立滑移的多套子模型,应用时根据应用领域的知识对样本归属作初步预估,然后程序选择相关的子模型进行判别归类。这种方法解决了由于时间序列多元数据周期性造成的样本分类颠倒问题,为时间序列数据的分类和预测开辟了新途径,在实际应用中取得了良好的效果,解决了重大难题。     

Covers of algebraic varieties III. The discriminant of a cover of degree 4 and the trigonal construction

For each Gorenstein cover of degree we define a scheme and a generically finite map of degree called the discriminant of . Using this construction we deal with smooth degree covers with . Moreover we also generalize the trigonal construction of S. Recillas.

     

Tamely Ramified Towers and Discriminant Bounds for Number Fields

The root discriminant of a number field of degree n is the nth root of the absolute value of its discriminant. Let R _2m be the minimal root discriminant for totally complex number fields of degree 2m, and put ₀ = lim inf _m R _2m . One knows that ₀ 4e 22.3, and, assuming the Generalized Riemann Hypothesis, ₀ 8e 44.7. It is of great interest to know if the latter bound is sharp. In 1978, Martinet constructed an infinite unramified tower of totally complex number fields with small constant root discriminant, demonstrating that ₀ < 92.4. For over twenty years, this estimate has not been improved. We introduce two new ideas for bounding asymptotically minimal root discriminants, namely, (1) we allow tame ramification in the tower, and (2) we allow the fields at the bottom of the tower to have large Galois closure. These new ideas allow us to obtain the better estimate ₀ < 83.9.     

A comparison of statistical methods for prenatal screening for Down syndrome

Currently, prenatal screening for Down Syndrome (DS) uses the mother's age as well as three biochemical markers for risk prediction. Risk calculations for the biochemical markers use a quadratic discriminant function. In this paper we compare several classification procedures to quadratic discrimination methods for biochemical-based DS risk prediction, based on data from a prospective multicentre prenatal screening study. We investigate alternative methods including linear discriminant methods, logistic regression methods, neural network methods, and classification and regression-tree methods. Several experiments are performed, and in each experiment resampling methods are used to create training and testing data sets. The procedures on the test data set are summarized by the area under their receiver operating characteristic curves. In each experiment this process is repeated 500 times and then the classification procedures are compared. We find that several methods are superior to the currently used quadratic discriminant method for risk estimation for these data. The implications of these results for prenatal screening programs are discussed.     

马田系统在数据分类中的应用

马田系统是一种新的模式识别技术,是将田口式信噪比的试验设计方法的一整套思想应用到模式识别的特征变量选择问题上,并通过构建正常样品的基准空间,应用马氏距离值进行样品类别的识别.探讨了马田系统的基本原理,并应用MTGS模型方法对费希尔关于鸢尾花类型的判别问题进行研究,显示了马田系统方法的良好判别分类效果.     

Quadratic extensions of totally real quintic fields

In this work, we establish lists for each signature of tenth degree number fields containing a totally real quintic subfield and of discriminant less than in absolute value. For each field in the list we give its discriminant, the discriminant of its subfield, a relative polynomial generating the field over one of its subfields, the corresponding polynomial over , and the Galois group of its Galois closure.

We have examined the existence of several non-isomorphic fields with the same discriminants, and also the existence of unramified extensions and cyclic extensions.

     

Inégalité du discriminant pour les pinceaux elliptiques à réductions quelconques

In this article the degree of the discriminant of an elliptic pencil on a projective curve is upper-bounded by using the degree of its conductor and the genus of the base curve. This is done in the most general case, extending a method and a result of Szpiro (1981 and 1990a) and a result of Hindry and Silvermann. The difficult part, dealing with characteristic 2 and 3 and additive reductions, need the introduction of a new object - which we called 'conducteur efficace' - defined by using differentials and interestingly comparable to the usual conductor. This article ends with a few results in the arithmetical case - case corresponding to an inequality conjectured by the second author in 1978: (1) the proof of this inequality in the potentially good reduction cases; (2) the passage from the semi-stable reduction to the general case for a strong inequality.     

一类交错级数的收敛定理

讨论和分析了一类交错级数的收敛问题,给出了异于莱布尼兹判别法的关于交错级数的一个收敛定理.我们的结论还推广了正项级数的拉阿伯判别法的使用范围.