一类二阶变系数线性微分方程的另二种解法

在文 [1 ]中我们介绍了二阶变系数线性方程y″+[b G( x) -G′( x)G( x) ]y′+c G2 ( x) y =0 ( 1 )的求解方法 (式中 G( x)在某区间 I上具有一阶连续导数 ,且 G( x)≠ 0 ,b和 c为实常数 ) ,即令y′=-G( x) yv ( 2 )将 ( 1 )化为关于新函数 v的一阶可分离变量方程 ,积分后代入 ( 2 )式再积分 ,最后得到方程 ( 1 )的通解。我们称这解法为函数变换降阶法。本文再介绍作者在文 [2 ]中给出的方程 ( 1 )的另二种解法。一、待定常数、函数法我们猜想方程 ( 1 )有形如y =erf (x) ( 3 )的解 ,其中 r为待定常数 ,f( x)为某一待定函数 ,它具有所需…     

齐次有理分式函数f(x,y)的极限存在判别法

本刊1981年第10期吴檀同志发表的一文“齐次有理分式函数f(x,y)的极限问题”中,给了齐次有理分式函数f(x,y)的极限存在判别法。为了开拓思路,扩大眼界,本文仅就上述的判别法给出一个新的证明。 设齐次有理分式函数f(x,y)=g(x,y)/h(x,y),其中g(x,y),h(x,y)分别是关于x,y的实系数的m次和n次     

求最小特征值的基于分段线性逼近的中介算子法

本文首先给出ρ(χ)为分段线性函数时,以方程y″ λρ(x)y=0 的特征值为零点的函数ω(λ),从而给出基于分段线性逼近的中介算子法,以求方程(p(x)y′)′ λq(x)y=0之最小特征值的上、下估计值。     

复合函数 f[φ(x)]图象的几何作法

函数是中学数学的重要概念之一,指导学生作好函数图象可以对函数的概念及其性质加强直观理解。中学课本上主要是用描点法来作图的,虽然二次函数和三角函数的图象也介绍了“平移法”。对于复合函数的图象如用描点法作图,常常先要讨论函数的性质,如定义域、单调性、奇偶生、周期性、极值等等,这就此较麻烦了。下面将介绍复合函数的几何作法。所谓复合函数就是:设Y=f(u),定义域为U,u= (x),其定义域为X,值域为U＇,若是UU＇,则称y为x的复合函数,记作y=f〔 (x)〕,其中u称为中间变量。中学课本上常见的函数,诸如y=lg(3x-1),y=sin(ωx+ ),y=1-x~2~(1/2)等等,就是复合函数。如果已知函数y=f(x)及y=(x)的图象,则用下列方法能作出y=f〔 (x)〕的图象。     

求三角函数周期的一种方法

在三角函数中,求周期是一个重要内容,也是一个难点。在常见的一些题目中,如求y=|sinx| |cosx|,y=(1-sinx)~(1/2) (1 sinx)~(1/2)的周期等一类,学生做起来总觉得不顺手,掌握比较困难,为了使这类问题易于解决,不妨试用“不变量函数方幂法”。什么叫“不变量函数方幂法”呢? 定义若函数y=f(x)在定义域A上恒非负,或者恒非正,则称函数y=f(x)为A上的不变量函数。定理若函数y=f(x)是定义在A上的不变量函数,且y=f~a(x)也是A上的不变量函数(a为非零有理数),则函数y=f(x)与y=     

两类一阶线性偏微分方程的解

利用二元复合函数求导的链式法则,推导一阶线性齐次偏微分方程P(x)f1x+Q(y)f1y=0的解,由此得出一阶线性非齐次偏微分方程P(x)f1x+Q(x)f1y=R(x)f和P(x) f1zx+Q(y)f1y=R(x)f的通解.     

全微分方程的不定积分解法及其证明

0　引言一个一阶微分方程写成P( x,y) dx +Q( x,y) dy =0 ( 1 )形式后 ,如果它的左端恰好是某一个函数 u=u( x,y)的全微分 :du( x,y) =P( x,y) dx +Q( x,y) dy那么方程 ( 1 )就叫做全微分方程。这里 u x=P( x,y) ,　　 u y=Q( x,y)方程 ( 1 )就是 du( x,y) =0 ,其通解为 :u( x,y) =C　 ( C为常数 )可见 ,解全微分方程的关键在于求原函数 u( x,y)。因此 ,本文将提供一种求原函数 u( x,y)的简捷方法 ,并给出证明。1　引入记号为了表述方便 ,先引入记号如下 :设 M( x,y)为一个含有变量 x,y项的二元函数 ,定义 :( 1 )“M( x,y)”表示 M(…     

Bernoulli方程解法的启迪

众所周知 ,Bernoulli方程dydx=P( x) y +Q( x) yn( n≠ 0 ,1 ) ( 1 )是可用初等积分法求解的一类非线性方程 ,其解法是用函数变换 z=y1- n,则方程 ( 1 )就化为关于未知函数 z的一阶性方程dzdx=( 1 -n) P( x) z +( 1 -n) Q( x)上述解法启迪我们提出一般的问题 :非线性微分方程dydx=P( x) f ( y) +Q( x) g( y) ( 2 )经函数变换化的一阶线性微分方程的充要条件是什么 ?又方程 ( 2 )经函数变换化为 Bernoulli方程的充要条件是什么 ?其中 P( x) ,Q( x)和 f( y) ,g( y)都分别是 x和 y的连续函数 ,且它们都不为零。定理 1　方程 ( 2 )经未知函…     

解微分方程时应注意的两点

笔者认为，初学者在解微分方程时，应注意两点：（一）注意变量x,y地位的对称性。即在判别微分方程的类型或解微分方程时，若按x为自变量、y为函数时不易处理，可转而考虑按x为自变量、x为函数时的情形。为便于应用，现说明如下：a．一阶齐次方程的两种形式：（这里x为自变量），或：生二。（半）（这里y为自变量）．””dH－”，“”““““““““””b．一阶线性微分方程的两种形式：dyn。、。，、，、。。、，。。，。、三十P（x）y一Q（x）（这里y为x的函数），dH“”—”“””—””““H““““。。。／，。dx、‘＾或三十P（…     

例析对函数创新型问题的探究

本文就函数的一些创新型问题作介绍与分析一、格点函数例1在直角坐标系中,横、纵坐标均为整数的点叫格点.若函数y=f(x)的图象恰好经过k个格点,则称函数y=f(x)为k阶格点函数.下列函数中为一阶格点函数的序号是     

工科数学教学中非逻辑思维能力训练初探

为在高等数学教学中培养学生的创造性思维能力,本文强调了在传统数学教学中容易忽视的“组合法”、“相似性法”、“列举奇想法”、“一题多解”等发散性思维能力的训练方法．     

Exact order of convergence of the secant method

We study the exact order of convergence of the secant method when applied to the problem of finding a zero of a nonlinear function defined from into . Under the standard assumptions for which Newton's method has the exact Q-order of convergencep, wherep is some positive integer, we establish that the secant method has the Q-order and the exact R-order of convergence . We prove also that, forp=2 andp=3, the secant method has the exact Q-order of convergenceS(p). Moreover, we present a counterexample to show that, forp4, it may not have an exact Q-order of convergence.The author wishes to thank Florian Potra, Richard Tapia, and the referees for helpful comments and suggestions.This paper was prepared while the author was Visiting Professor, Department of Mathematics, University of Kentucky, Lexington, Kentucky.     

Sphere of Convergence of Newton's Method on Two Equivalent Systems from Nonlinear Programming

We study a local feature of two interior-point methods: a logarithmic barrier function method and a primal-dual method. In particular, we provide an asymptotic analysis on the radius of the sphere of convergence of Newton's method on two equivalent systems associated with the two aforementioned interior-point methods for nondegenerate nonlinear programs. We show that the radii of the spheres of convergence have different asymptotic behavior, as the two methods attempt to follow a solution trajectory {x } that, under suitable conditions, converges to a solution as 0. We show that, in the case of the barrier function method, the radius of the sphere of convergence of Newton's method is (), while for the primal-dual method the radius is bounded away from zero as 0. This work is an extension of the authors earlier work (Ref. 1) on linear programs.     

Rate of convergence of a generalization of Newton's method

The Newton's method for finding the root of the equation (t)=0 can be easily generalized to the case where is monotone, convex, but not differentiable. Then, the convergence is superlinear. The purpose of this note is to show that the convergence is only superlinear. Indeed, for all (1, 2), we exhibit an example where the convergence of the iterates is exactly .     

Design of Civil Engineering Frame Structures Using a Monomial/Newton Hybrid Method

This paper presents an application of a monomial approximation method for solving systems of nonlinear equations to the design of civil engineering frame structures. This is accomplished by solving a set of equations representing the state known as fully-stressed design, where each member of the structure is stressed to the maximum safe allowable level under at least one of the loading conditions acting on it. The monomial approximation method is based on the process of condensation, which has its origin in geometric programming theory. A monomial/Newton hybrid method is presented which permits some of the design variables to be free in sign, while others are strictly positive. This hybrid method is well suited to the structural design application since some variables are naturally positive and others are naturally free. The proposed method is compared to the most commonly used fully-stressed design method in practice. The hybrid method is shown to find solutions that the conventional method cannot find, while doing so with less computational effort. The impact of this approach on the activity of structural design is discussed.     

“另一个25阶最大平面图”G′_(M25)的四色着色

利用最大平面图着色的"简化降阶法",对一定拓扑结构的"另一个25阶最大平面图"G′_(M25)进行了着色运作.先逐点"降阶",再逐点"着色、升阶、着色",直至获得G′_(M25)的四色着色方案.由于着色过程中,有些点的着色是可以选择的,在这些点作任意选色后,只是找出其中的二个G′_(M25)的四色着色方案,即"四色着色方案壹"和"四色着色方案贰"(其他的四色着色方案未作求解).然后,在"四色着色方案壹"和"四色着色方案贰"的基础上,利用多层次的"二色交换法",相应地分别求出了G′_(M25)的二个相近四色着色方案集,即"相近四色着色方案集壹"和"相近四色着色方案集贰".在"相近四色着色方案集壹"中,含有72个不同的四色着色方案;在"相近四色着色方案集贰"中,含有156个不同的四色着色方案.文中对这二个相近四色着色方案集进行了分析,得到了有意义的结果.     

Convergence of approximate solution of system of Fredholm integral equations

In this paper numerical solution of system of linear Fredholm integral equations by means of the Sinc-collocation method is considered. This approximation reduces the system of integral equations to an explicit system of algebraic equations. The exponential convergence rate of the method is proved. The method is applied to a few test examples with continuous kernels to illustrate the accuracy and the implementation of the method.     

A new eighth-order iterative method for solving nonlinear equations

In this paper we present an improvement of the fourth-order Newton-type method for solving a nonlinear equation. The new Newton-type method is shown to converge of the order eight. Per iteration the new method requires three evaluations of the function and one evaluation of its first derivative and therefore the new method has the efficiency index of , which is better than the well known Newton-type methods of lower order. We shall examine the effectiveness of the new eighth-order Newton-type method by approximating the simple root of a given nonlinear equation. Numerical comparisons are made with several other existing methods to show the performance of the presented method.     

Real Solving of Elementary-Algebraic Systems

In this paper we present a new method for enclosing all the real roots in a bounded box of a system of n elementary-algebraic equations depending on n variables. This system is denoted by h(x)=P(x,f ₁(x ₁),...,f _k (x ₁),f ₁(x ₂),...,f _k (x _n )), where x=(x ₁,x ₂,...,x _n ) R ⁿ , P is a system of polynomials depending on n+kn variables and the univariate functions f _i are simple. This method arises from the exclusion method of Dedieu and Yakoubsohn. We provide both a theoretical complexity bound and some numerical experiments.