How to use the method of the improvising differentiation？

We know the Substitution Rule, which is based on the following identity in differentiation.∫f（g（x））g＇（x）dx=∫（u）du（where u= g（x）） . Now, we＇ll talk about how to use the method of the improvising differentiation, and give some examples by using basic integration formulas, such as,∫（1/x）dx=1n｜x｜＋C called the Log Rule for integration,∫e^x dx=e^x＋C called the Exponential Rule.     

What is the differential equation？

An equation involving a derivative is called a differential equation.Such as,dy/dx=2x,and the function y=f（x）satisfies this equation.When we know the additional condition that y=2 when x=-1,the function y=f（x）will be find exactly.The additional condition is called the initial condition.It is used to evaluate constant of integration.     

Existence of Renormalized Solutions for Nonlinear Parabolic Equations

We give an existence result of a renormalized solution for a class of nonlin- ear parabolic equations b（x,u）/ t-div （a（x,t,u, u））＋g（x,t,u,u ）＋H（x,t, u）=f,in QT, where the right side belongs to LP＇ （0,T;W-1,p＇（Ω）） and where b（x,u） is unbounded function of u and where - div （ a （ x, t, u, u） ） is a Leray-Lions type operator with growth ｜u ｜p- 1 in V u. The critical growth condition on g is with respect to u and no growth condition with re sp ect to u, while the function H （x, t, u） grows as｜ u ｜p - 1.     

Existence of Positive Solutions to Semipositone Singular Dirichlet Boundary Value Problems

The paper presents the conditions which guarantee that for some positive value of μ there are positive solutions of the differential equation （Ф（x＇））＇＋μQ（t, x, x＇） = 0 satisfying the Dirichlet boundary conditions x（0） = x（T） = 0. Here Q is a continuous function on the set [0, T] × （0, ∞） ~ （R ／ {0}） of the semipositone type and Q is singular at the value zero of its phase variables.     

Inverse Functions of Number-Theoretic Functions (I)

If gf(x) =x for every x, then g is called a left inverse function of f and f is a right inverse function of g. If f is both left and right inverse function of g, then f and g are said to be mutually inverse to each other. We show that (§ 1) the following results hold. A function f has a left inverse if and only if f is univalent, a function g has a right inverse if and only if g is exhaustive, i. e., g takes every (natural) number as values. Hence f has both left and right inverse if and only if f is both univalent and exhaustive, i. e., f is a permutation on the domain of natural numbers. Let g_1 and g_2 be two left inverse functions of the function f. If for every left inverse g of f, we have $g_1(x) \leq g(x) \leq g_2(x)$, then g_1(x) is called the weak, and g_2(x) is the strong, left inverse function of f. Similarly we define the weak and the strong right inverse functions. We show that(§ 2) every strict increasing function f must possess weak and strong left inverse functions, and all of its left inverse functions must be exhaustive slow increasing (a function g(x) is slow increasing if and only if g(Sx) —Sg(x) =0, here s denotes the successor function). On the other hand, every exhaustive function g must possess weak and strong right inverse functions, and all of its right inverse functions must strict increasing. We show also that (§ 3): If f_1(x) and f_2(x) both take g(x) as their strong (weak) left inverse, then f_1(x)=f_2(x)(f_1(Sx)=f_2(Sx)). If g_1(x) and g_2(x) both take f(x) as their strong or weak right inverse, then g_1(x)=g_2(x). From these results we see that we may find a function from its strong (weak) left or right inverse function. Let there be f(c) \leq x 相似文献   

EXISTENCE AND UNIQUENESS FOR SECOND-ORDER VECTOR BOUNDARY VALUE PROBLEM OF NONLINEAR SYSTEMS

This paper is concerned with the following second-order vector boundary value problem ：x^R=f（t,Sx,x,x＇）,0〈t〈1,x（0）=A,g（x（1）,x＇（1））=B,where x,f,g,A and B are n-vectors. Under appropriate assumptions,existence and uniqueness of solutions are obtained by using upper and lower solutions method.     

Implicit function theorem and its application to a Ulam’s problem for exact differential equations

We prove a global version of the implicit function theorem under a special condition and apply this result to the proof of a modified Hyers-Ulam-Rassias stability of exact differential equations of the form, g（x, y） ＋ h（x, y）y＇ =0.     

EXACT AND DISCRETIZED DISSIPATIVITY OF THE PANTOGRAPH EQUATION

The analytic and discretized dissipativity of nonlinear infinite-delay systems of the form x＇（t） = g（x（t）,x（qt））（q∈ （0, 1）, t 〉 0） is investigated. A sufficient condition is presented to ensure that the above nonlinear system is dissipative. It is proved the backward Euler method inherits the dissipativity of the underlying system. Numerical examples are given to confirm the theoretical results.     

ON THE DIVIDED DIFFERENCE FORM OF FAA DI BRUNO＇S FORMULA Ⅱ

In this paper, we consider the higher divided difference of a composite function f（g（t）） in which g（t） is an s-dimensional vector. By exploiting some properties from mixed partial divided differences and multivariate Newton interpolation, we generalize the divided difference form of Faà di Bruno＇s formula with a scalar argument. Moreover, a generalized Faà di Bruno＇s formula with a vector argument is derived.     

Semi-empiricial Likelihood Confidence Intervals for the Differences of Two Populations Based on Fractional Imputation

Suppose that there are two populations x and y with missing data on both of them, where x has a distribution function F（·） which is unknown and y has a distribution function Gθ（·） with a probability density function gθ（·） with known form depending on some unknown parameter θ. Fractional imputation is used to fill in missing data. The asymptotic distributions of the semi-empirical likelihood ration statistic are obtained under some mild conditions. Then, empirical likelihood confidence intervals on the differences of x and y are constructed.     

Multiplicative Mappings of Rings

Let R and F be arbitrary associative rings. A mapping φ of R onto F is called a multiplicative isomorphism if φ is bijective and satisfies φ（xy） = φ（x）φ（y） for all x, y ∈ R. In this short note, we establish a condition on R, in the case where R may not contain any non-zero idempotents, that assures that φ is additive, which generalizes the famous Martindale＇s result. As an application, we show that under a mild assumption every multiplicative isomorphism from the radical of a nest algebra onto an arbitrary ring is additive.     

Existence of Solutions to a Singular Initial Value Problem

Under the sign assumptions we investigate the global existence of solutions of the initial value problem x＇ =f（t, x, x＇）, x（0） = A, where the scalar function f（t, x,p） may be singular at x = A.     

Linearly McCoy Rings and Their Generalizations

A ring R is called linearly McCoy if whenever linear polynomials f（x）, g（x） e R[x]／{0） satisfy f（x）g（x） ： O, then there exist nonzero elements r, s ∈ R such that f（x）r ： sg（x） =0. For a ring endomorphism α, we introduced the notion of α-skew linearly McCoy rings by considering the polynomials in the skew polynomial ring R[x; α] in place of the ring R[x]. A number of properties of this generalization are established and extension properties of α-skew linearly McCoy rings are given.     

On the Non-Commutative Neutrix Product of the Distributions x＋^λ and x^＋μ

Let f and g be distributions and let gn = （g ＊ δn）（x）, where δn （x） is a certain converging to the Dirac delta function. The non-commutative neutrix product fog of f and g to be the limit of the sequence {fgn }, provided its limit h exists in the sense that sequence is defined N-lim n-∞（f（x）g,, （x）, φ（x）〉 = （h（x）, φ（x）},for all functions p in 2. It is proved that （x^λ＋1n^px＋）0（x^μ＋1n^qx＋）=x＋^λμ1n^p＋qx＋,（x^λ-1n^qx-）=x-^λ＋μ1n^p＋qx-,for λ＋μ〈-1; λ,μ, λ＋μ≠-1,-2…and p,q=0,1,2……     

What is the linear approximation?(1)

If a function f(x) is differentiable,then the linear approximation of f(x) at a is f(x)≈f(a)+f′(a)(x-a),while the value of x close to a.The equation L(x)=f(a)+f′(a)(x-a) is called the linearization of f(x) at a.     

Large deviations and moderate deviations for kernel density estimators of directional data

Let fn be the non-parametric kernel density estimator of directional data based on a kernel function K and a sequence of independent and identically distributed random variables taking values in d-dimensional unit sphere Sd-1. It is proved that if the kernel function is a function with bounded variation and the density function f of the random variables is continuous, then large deviation principle and moderate deviation principle for {sup x∈sd-1 ｜fn（x） - E（fn（x））｜, n ≥ 1} hold.     

Uniform convergence of wavelet solution to the sideways heat equation

We consider the problem uxx（x, t） = ut（x, t）, 0 ≤ x 〈 1, t ≥ 0, where the Cauchy data g（t） is given at x = 1. This is an ill-posed problem in the sense that a small disturbance on the boundary g（t） can produce a big alteration on its solution （if it exists）. We shall define a wavelet solution to obtain the well-posed approximating problem in the scaling space Vj. In the previous papers, the theoretical results concerning the error estimate are L2-norm and the solutions aren＇t stable at x = 0. However, in practice, the solution is usually required to be stable at the boundary. In this paper we shall give uniform convergence on interval x ∈ [0, 1].     

Inverse of a Function f（x）=y

For a function y= f（x） to have an inverse function, f must be one-to-one. Then for each x in its domian there is exactly one y in its range; furthermore, to each y in the range, there corresponds exactly one x in the domain. The correspondence from the range of f onto the domian of f is, therefore, also a function. It is this function that is the inverse of f.     

Global Attractivity of Positive Periodic Solutions for a Survival Model of Red Blood Cells

In this paper, we deal with a model for the survival of red blood cells with periodic coefficients x＇（g）=-μ（t）x（t）＋P（t）e^-γ（t）x（t-τ（t））,t≥0.（＊）A new sufficient condition for global attractivity of positive periodic solutions of Eq. （＊） is obtained. Our criterion improves corresponding result obtained by Li and Wang in 2005.     

Logarithmic Function

Recall that a one-to-one function y= f（x） has an inverse function that is defined （implicitly） by the equation x= f（y）, In particular, the exponential function：