等差项乘积的渐进估计

研究了等差项乘积∏ni=1a_i的渐进估计.首先给出了一系列关于等差项乘积的不等式,继而应用Euler-Maclaurin求和公式及Γ函数的Stirling公式:Γ(x+1)~(2πx)~(1/2)(x/e)~x(x→+∞),推导出了∏ni=1a_i的较精确的渐进式,最后,得到了精确化的Wallis公式.     

苏联莫斯科大学1989年入学考试试题及解答

数学力学系卷1 1.解方程(3~(8xctgπx))~x27~(5xctgπx)=9~(ctgπx)。2.解不等式[log(8-2)~(1/2)(2x-1)][log_2(1+2x-x~2)]≥0。3.一条直线经过△ABC的顶点A和平行于边AC的中位线的中点,问这条直线分这个三角形成两部分的面积之比是多少? (如图1)     

国外试题选登

<正> (苏)(1)求极限(2)设x>0时,f(x)=(1+x)~(1/(?)),证明当x→0~+时,f(x)-e+Ax+Bx~2+o(x~2),并求A、B两常数. (3)证明不等式(sinx)~(-2)≤x~(-2)+1-(4/(π~2))x∈(0,(π/2)).     

2015年新课标(Ⅰ)卷数学(理)第12题解法的探究

<正>一、试题呈现题目(2015年新课标(Ⅰ)理12)设函数f(x)=e~x(2x-1)-ax+a,其中a<1,若存在唯一的整数x_0,使得f(x_0)<0,则实数a的取值范围是().(A)[-3/2e,1)(B)[-3/2e,3/4)(C)[3/2e,3/4)(D)[3/2e,1)二、思路分析本题是有关不等式的存在性恒成立问题,难点是不等式的解是整数,但处理的方法与一般性的恒成立问题并无本质区别,解决这类问题通常有三种思路:     

共轭Bochner—Riesz平均在H~p上的弱型估计

设K(x)=P(x/|x|)|x|~(-n)为一球调和核,P(x)为一m次齐次调和多项式。f(x)在R~n上的δ阶共轭Bochner-Riesz平均记为 (_(1/ε)~δf)(x)=∫_(|t|<1/ε)(t)(t)(1-|εt|~2)~δe~(iαt)dt.作者在本文中得到如下的弱型估计: |{x∈R~n:sup ε>0|(_(1/ε)~δf)(x)-_ε(x)|>λ}|≤C(‖f‖_(H~p)/λ)~p,此处δ=(n/p)-(n 2)/2,n/(n 1)≤p<1,f∈H~p(R~n),以及 _ε(x)=(2π)~(-n)∫_(|y|>ε)f(x-y)K(y)dy 。设f∈L(R~n),其δ阶的Bochner-Riesz平均为 (σ_(1/ε)~δf)(x)=∫_(|t|<1/ε)(t)(1-|εt|~2)~δe~(iαt)dt.     

THE BEST APPROXIMATION CONSTANT FOR THE JACKSON''''S TYPE OPERATOR J_(n,3) (f;x)

In this paper we obtain the best approximation constant of function f(x)(∈C_(2π))by theJackson's type operator J_(π3)(f;x),i.e.‖J_(n,3)(f,x)-f(x)‖_c≤(4-6/π)ω(f,1/n),‖J_(n,3)(f,x)-f(x)‖_c≤(8-17/π)ω_2(f,1/n)     

高中数学同步训练 第六章 反三角函数和三角方程

§1 反三角函数的概念一、选择题 1.适合不等式arccos3x〉3的x的集合是( ) (A){x|0≤x相似文献   

运用重要极限lim x→0(1+x)~(?/x)=e求极限时的一个简便方法

<正> 运用重要极限lim(1+x)~(1/x)=e(或lim(1+1/x)~x=e)求极限是求未定式“1~∞”型极限的一个重要方法。例如:     

Kloosterman sums with multiplicative coefficients

Let f(n)be a multiplicative function satisfying |f(n)|≤1,q(≤N~2)be a positive integer and a be an integer with(a,q)= 1.In this paper,we shall prove that ∑n≤N(n,q)=1f(n)e(an/q)■(1/2)(τ(q)/q)N loglog(6N)+ q~(1/4+ε/2)N~(2/1)(log(6N))~(1/2)+N/(1/2)(loglog(6N)),where n is the multiplicative inverse of n such that nn ≡ 1(mod q),e(x)= exp(2πix),and τ(·)is the divisor function.     

I.Schur问题的推广及证明

本文推广了Ⅰ.Schur 关于数列的三个结果,证明了函数 f(x)=(1+1/x)~(x+p_1)(x>0),g(x)=(1+1/x)~x(1+(p_2)/x)(x>0)与 h(x)=(1+p_3/x)~(x+1)(x>max{0,-P_3})单调下降充要条件,分别为 p_1≥1/2,p_2≥1/2与0相似文献   

Sharp Inequalities Involving $$(n!)^{1/n}$$

We prove that, for all integers \(n\ge 1\),

$$\begin{aligned} \Big (\sqrt{2\pi n}\Big )^{\frac{1}{n(n+1)}}\left( 1-\frac{1}{n+a}\right) <\frac{\root n \of {n!}}{\root n+1 \of {(n+1)!}}\le \Big (\sqrt{2\pi n}\Big )^{\frac{1}{n(n+1)}}\left( 1-\frac{1}{n+b}\right) \end{aligned}$$

and

$$\begin{aligned} \big (\sqrt{2\pi n}\big )^{1/n}\left( 1-\frac{1}{2n+\alpha }\right) <\left( 1+\frac{1}{n}\right) ^{n}\frac{\root n \of {n!}}{n}\le \big (\sqrt{2\pi n}\big )^{1/n}\left( 1-\frac{1}{2n+\beta }\right) , \end{aligned}$$

with the best possible constants

$$\begin{aligned}&a=\frac{1}{2},\quad b=\frac{1}{2^{3/4}\pi ^{1/4}-1}=0.807\ldots ,\quad \alpha =\frac{13}{6} \\&\text {and}\quad \beta =\frac{2\sqrt{2}-\sqrt{\pi }}{\sqrt{\pi }-\sqrt{2}}=2.947\ldots . \end{aligned}$$

     

An ultimate extremely accurate formula for approximation of the factorial function

We prove in this paper that for every x ≥ 0,

Clifford 环面 Sm(\sqrt{\frac{m}{n}})×Sn-m(\sqrt{\frac{n-m}{n}})的刚性定理

\small\zihao{-5}\begin{quote}{\heiti 摘要:} 设$M$为$n+1$维单位球面$S^{n+1}(1)$中的一个极小闭超曲面，如果 $ n \le S \le n+\frac{2}{3}$, 则有 $S=n$ 且 $M$ 与某一Clifford 环面 $S^m(\sqrt{m/n}) \times S^{n-m}(\sqrt{(n-m)/n})$等距.     

Two families of approximations for the gamma function

In this paper, we establish two families of approximations for the gamma function: $$ \begin{array}{lll} {\varGamma}(x+1)&=\sqrt{2\pi x}{\left({\frac{x+a}{{\mathrm{e}}}}\right)}^x {\left({\frac{x+a}{x-a}}\right)}^{-\frac{x}{2}+\frac{1}{4}} {\left({\frac{x+b}{x-b}}\right)}^{\sum\limits_{k=0}^m\frac{{\beta}_k}{x^{2k}}+O{{\left(\frac{1}{x^{2m+2}}\right)}}},\\ {\varGamma}(x+1)&=\sqrt{2\pi x}\cdot(x+a)^{\frac{x}{2}+\frac{1}{4}}(x-a)^{\frac{x}{2}-\frac{1}{4}} {\left({\frac{x-1}{x+1}}\right)}^{\frac{x^2}{2}}\\ &\quad\times {\left({\frac{x-c}{x+c}}\right)}^{\sum\limits_{k=0}^m\frac{{\gamma}_k}{x^{2k}}+O{\left({\frac{1}{x^{2m+2}}}\right)}}, \end{array}$$ where the constants ${\beta }_k$ and ${\gamma }_k$ can be determined by recurrences, and $a$ , $b$ , $c$ are parameters. Numerical comparison shows that our results are more accurate than Stieltjes, Luschny and Nemes’ formulae, which, to our knowledge, are better than other approximations in the literature.     

Hermite Expansion of the Riemann Zeta Function

Let $ζ(s)$ be the Riemann zeta function, $s=\sigma+it$. For $0 < \sigma < 1$, we expand $ζ(s)$ as the following series convergent in the space of slowly increasing distributions with variable $t$ : $$ζ(\sigma+it)=\sum\limits^∞_{n=0}a_n(\sigma)ψ_n(t),$$ where $$ψ_n(t)=(2^nn!\sqrt{\pi})^{-1 ⁄ 2}e^{\frac{-t^2}{2}}H_n(t),$$ $H_n(t)$ is the Hermite polynomial, and $$a_n(σ)=2\pi(-1)^{n+1}ψ_n(i(1-σ))+(-i)^n\sqrt{2\pi}\sum\limits^∞_{m=1}\frac{1}{m^σ}ψ_n(1nm).$$ This paper is concerned with the convergence of the above series for $σ > 0.$ In the deduction, it is crucial to regard the zeta function as Fourier transfomations of Schwartz' distributions.     

A new Stirling series as continued fraction

We introduce the following new Stirling series

$ n!\sim \sqrt{2\pi n}\left( \frac{n}{e}\right) ^{n}\exp \frac{1}{12n+\frac{ \frac{2}{5}}{n+\frac{\frac{53}{210}}{n+\frac{\frac{195}{371}}{n+\frac{\frac{ 22,\!999}{22,\!737}}{n+\ddots}}}}}, $

as a continued fraction, which is faster than the classical Stirling series.

     

Convergence of Solutions of General Dispersive Equations Along Curve

In this paper, the authors give the local L~2 estimate of the maximal operator S_(φ,γ)~* of the operator family {S_(t,φ,γ)} defined initially by ■which is the solution(when n = 1) of the following dispersive equations(~*) along a curve γ:■where φ : R~+→R satisfies some suitable conditions and φ((-?)~(1/2)) is a pseudo-differential operator with symbol φ(|ξ|). As a consequence of the above result, the authors give the pointwise convergence of the solution(when n = 1) of the equation(~*) along curve γ.Moreover, a global L~2 estimate of the maximal operator S_(φ,γ)~* is also given in this paper.     

Γ-Convergence of some super quadratic functionals with singular weights

We study the Γ-convergence of the following functional (p > 2)

Error function inequalities

We present various inequalities for the error function. One of our theorems states: Let α?≥?1. For all x,y?>?0 we have $$ \delta_{\alpha} < \frac{ \mbox{erf} \left( x+ \mbox{erf}(y)^{\alpha}\right) +\mbox{erf}\left( y+ \mbox{erf}(x)^{\alpha}\right) } {\mbox{erf}\left( \mbox{erf}(x)+\mbox{erf}(y)\right) } < \Delta_{\alpha} $$ with the best possible bounds $$ \delta_{\alpha}= \left\{ \begin{array}{ll} 1+\sqrt{\pi}/2, & \ \ \textrm{{if} $\alpha=1$,}\\ \sqrt{\pi}/2, & \ \ \textrm{{if} $\alpha>1$,}\\ \end{array}\right. \quad{\mbox{and} \,\,\,\,\, \Delta_{\alpha}=1+\frac{1}{\mbox{erf}(1)}.} $$      

A concentrated Cauchy distribution with finite moments

The Cauchy distribution $$\mathfrak {C}(a,b)(x)=\frac{1}{\pi b(1+(\frac{x-a}{b})^2)},\quad -\infty < x <\infty,$$ with a,b real, b>0, has no moments (expected value, variance, etc.), because the defining integrals diverge. An obvious way to “concentrate” the Cauchy distribution, in order to get finite moments, is by truncation, restricting it to a finite domain. An alternative, suggested by an elementary problem in mechanics, is the distribution $${\mathfrak {C}}_g(a,b)(x)=\frac{\sqrt{1+2 b g}}{\pi b (1+(\frac{x-a}{b})^2)\sqrt{1-2 b g(\frac{x-a}{b})^2}},\quad a-\sqrt{\frac{b}{2g}}<x<a+\sqrt{\frac{b}{2g}},$$ with a,b as above and a third parameter g≥0. It has the Cauchy distribution C(a,b) as the special case with g=0, and for any g>0, ? _g (a,b) has finite moments of all orders, while keeping the useful “fat tails” property of ?(a,b).