一类级数求和的推广

借助收敛级数的简单运算,对一类简单级数及和数进行四种形式的推广.     

两个级数求和问题的概率模型

通过构造概率模型,应用概率论与数理统计的方法给出两个特殊级数的求和问题.     

一类级数的求和

给出了一类级数的求和公式,并列举其应用.     

与中心数相关的一类级数求和公式

This paper provides a pair of summation formulas for a kind of combinatorial series involvingak＋b m as a factor of the summand. The construction of formulas is based on a certain series transformation formula [2, 7, 9] and by making use of the C-numbers [3]. Various consequences and examples including several remarkable classic identities are presented to illustrate some applications of the formulas obtained.     

关于级数的求和方法

高等数学关于级数的研究中，讨论了常数项级数的敛散性以及函数项级数的收敛域．但对收敛的常数项级数的求和以及在收敛域内如何求函数项级数的和函数讨论不多．级数的求和方法比较多，技巧性也比较强，下面介绍常用的有效的级数求和方法。     

一类无穷级数的求和

利用解微分方程的方法得到一类幂级数的和函数,作为其特例可求得一类数项级数的和．     

一类无穷级数的求和

利用解微分方程的方法得到一类幂级数的和函数,作为其特例可求得一类数项级数的和.     

两个级数的求和问题

本文讨论级数(1)和级数(2)的求和问题,得出其求和公式(3)、(4).     

级数求和方法

级数求和是级数理论的基本问题之一,也是较难解决的问题.本文将从几个不同的角度对级数求和的方法作一探讨.     

一类级数的和及其应用

本“着重”论鑫赵客点导升这口忿(2)E.二劣.七面类级数的求和问题,并利用所得的结果计算伯努里(Be,nooll落)数B。与欧拉(Eole,)数E。及一类广义积分.{勺巴一J oeh卫鱼“一2{.劣2*e一,01+e一,‘2丝里迩丝l矛~上卫达二 “:‘+’岔(Zn一1)“+’l.、预备知识函数项级数②劣,含eos介劣心习x,介一’e一’“’‘二22七一l‘3,号{协.1劣2卜le一2.二 1一e一2.刃e2.苦一1,在任意闭区间〔叮,A〕(O<刀相似文献   

一类级数求和的推广之注记

通过对文献[1]中结论的分析,进一步阐述了拆项技巧在级数求和中的应用.     

一个除数问题的推广

本文推广了Ｒ．Ａ．Ｓｍｉｔｈ，Ｍ．Ｖ．Ｓｕｂｂａｒａｏ和Ｇ．Ｎｏｗａｋ所考虑的一个除数问题．令Ｓ＝｛（ａｉ，ｑｉ）｜ａｉ≤ｑｉ｝（ｒ≥３）．定义ｄ（ｎ；Ｓ）＝Σ（１）１，Σ（１）表示对满足ｎ＝ｍ１…ｍｒ，ｍｊ≡ａｊ（ｍｏｄｑｊ），ｊ＝１，２，…，ｒ的诸ｍｊ求和．我们求出了Σｎ≤ｘｄ（ｎ；Ｓ）的渐近公式，并得到了余项估计．     

Summation of Fourier Series on the Infinite-Dimensional Torus

Conditions for the convergence of Fejér means for functions on the infinite-dimensional torus over cubes and rectangles are obtained, and a generalization of these results to the case of products of abstract measure spaces is proposed.

     

矩阵幂和问题的进一步讨论

本文证明了;(1)F_p~m上p~m次幂矩阵的充要条件;(2)F_p~m上任一方阵都可表示为2个其最小多项式均无重因式的q次幂矩阵之和;(3)任一整数方阵可表示成不超过7个平方次幂整数矩阵之和,从而推广和改进了文[1,2]的结果.     

On Summation of Nonharmonic Fourier Series

Let a sequence \(\Lambda \subset {\mathbb {C}}\) be such that the corresponding system of exponential functions \({\mathcal {E}}(\Lambda ):=\left\{ {\text {e}}^{i\lambda t}\right\} _{\lambda \in \Lambda }\) is complete and minimal in \(L^2(-\pi ,\pi )\), and thus each function \(f\in L^2(-\pi ,\pi )\) corresponds to a nonharmonic Fourier series in \({\mathcal {E}}(\Lambda )\). We prove that if the generating function \(G\) of \(\Lambda \) satisfies the Muckenhoupt \((A_2)\) condition on \({\mathbb {R}}\), then this series admits a linear summation method. Recent results show that the \((A_2)\) condition cannot be omitted.     

一个最值问题的推广

最值问题是微积分应用的典型问题之一.某些经典教材中,应用微分工具解决货物运输过程中运费最省问题的方法,将被拓展成一般的解法原理,同时给出这种原理的实际应用.     

On the Generalization Problem

The generalization problem considered in this paper assumes that a limited amount of input and output data from a system is available, and that from this information an estimate of the output produced by another input is required. The ideas arose in the study of neural networks, but apply equally to any approximation approach. The main result is that the type of neural network to be used for generalization should be determined by the prior knowledge about the nature of the output from the system. Without such information, either of two networks matching the training data is equally likely to be the better at estimating the output generated by the same system at a new input. Therefore, the search for an optimum generalization network for use on all problems is inappropriate.For both (0, 1) and accurate real outputs, it is shown that simple approximations exist that fit the data, so these will be equally likely to generalize better than more sophisticated networks, unless prior knowledge is available that excludes them. For noisy real outputs, it is shown that the standard least squares approach forces the neural network to approximate an incorrect process; an alternative approach is outlined, which again is much easier to learn and use.     

Euler-Maclaurin Summation of Trigonometric Fourier Series

Trigonometric Fourier series are, in general, difficult to sum to high accuracy. An example is given by the series in which α and β(>0) are rational numbers satisfying 0<β/α≤1, where λ is an independent variable and j is a positive integer or zero. This paper presents a method for the efficient evaluation of the sum of such series. Fourier series which are the real or the imaginary part of , but which are not explicitly expressible as simple polynomials in λ, are obtained as the sum of a logarithic term and an infinite series in powers of λ, whose expansion is valid when 0<λ≤(2π/α) and is exact. When the Fourier series is expressible as a polynomial in λ, the method identifies that polynomial.