Fractal interpolation: a sequential approach

Fractal interpolation is a modern technique to fit and analyze scientific data. We develop a new class of fractal interpolation functions which converge to a data generating(original) function for any choice of the scaling factors. Consequently, our method offers an alternative to the existing fractal interpolation functions(FIFs). We construct a sequence of α-FIFs using a suitable sequence of iterated function systems(IFSs). Without imposing any condition on the scaling vector, we establish constrained interpolation by using fractal functions. In particular,the constrained interpolation discussed herein includes a method to obtain fractal functions that preserve positivity inherent in the given data. The existence of Cr-α-FIFs is investigated. We identify suitable conditions on the associated scaling factors so that α-FIFs preserve r-convexity in addition to the C~r-smoothness of original function.     

Periodic Solutions of Evolution Variational Inequalities — a Method of Guiding Functions

This paper focuses on a part of the presentation given by the third author at the Shanghai Forum on Industrial and Applied Mathematics （Shanghai 2006）. It is related to the existence of a periodic solution of evolution variational inequalities. The approach is based on the method of guiding functions.     

某些循环对称多连通域弹性平面问题

In this paper, some lemmas of the analytic functions in unite disk are extented tothe automorphic functions with respect to a finite group. With the help of these lem-mas, some plane plastic problems on the cirular symmetric region are discussed. Finally,by means of a numerical example is given the method of undetermined coefficient.     

直接法的推广与广义Burgers方程的条件对称约化

A generalization of the direct method of Clarkson and Kruskal for finding similarity reductions of partial differential equations with arbitrary functions is found and discussed for the generalized Burgers equation. The corresponding reductions and the exact solutions due to the methods of the ordinary differential equations are then given by the methods. The results given here answer partially an open problem proposed by Clarkson, that is how to develop the direct method to seek symmetry reductions of nonlinear PDEs with arbitrary functions.     

Approximating conditional density functions using dimension reduction

We propose to approximate the conditional density function of a random variable Y given a dependent random d-vector X by that of Y given θ^τX, where the unit vector θ is selected such that the average Kullback-Leibler discrepancy distance between the two conditional density functions obtains the minimum. Our approach is nonparametric as far as the estimation of the conditional density functions is concerned. We have shown that this nonparametric estimator is asymptotically adaptive to the unknown index θ in the sense that the first order asymptotic mean squared error of the estimator is the same as that when θ was known. The proposed method is illustrated using both simulated and real-data examples.     

Histogram-kernel error and its application for bin width selection in histograms

Histogram and kernel estimators are usually regarded as the two main classical data-based non- parametric tools to estimate the underlying density functions for some given data sets. In this paper we will integrate them and define a histogram-kernel error based on the integrated square error between histogram and binned kernel density estimator, and then exploit its asymptotic properties. Just as indicated in this paper, the histogram-kernel error only depends on the choice of bin width and the data for the given prior kernel densities. The asymptotic optimal bin width is derived by minimizing the mean histogram-kernel error. By comparing with Scott’s optimal bin width formula for a histogram, a new method is proposed to construct the data-based histogram without knowledge of the underlying density function. Monte Carlo study is used to verify the usefulness of our method for different kinds of density functions and sample sizes.     

具有超解析Cauchy核的奇异积分方程

We investigate the solvability and the solving methods of singular integral equation with hyperanalytic Cauchy kernel(?) where α,k are hypercomplex functions in the sense of A. Douglis, φ is the unknown function. We prove that the equation Kφ=f , under certain conditions, is Noetherian. And a direct method to solve Kφ = f whenα and k are the boun dary values of hyperanalytic functions is given.     

The Partial Stability for Linear Discrete Systems

In this paper, we study the partial stability of linear discrete systems by means of Liapunov's functions of quadratic form. We obtain a necessary and sufficient condition for the system being stable with respect to part of variables and generalize Liapunov's equation to the partial stability of linear discrete systems. A method of constructing Liapunov's function of quadratic form for the stability of the systems is given.     

AN APPROACH TO DESIGN OBSERVER FOR A CLASS OF DISCRETE CONTROL SYSTEMS WITH TIME-DELAY

The design of functional observer for a class of discrete systems with time-delay is concerned. The solution to Sylvester function is given. An improved method for the functional observer design is proposed by the condition of linear matrix inequality. In the end,an example is given to illustrate the feasibility of the method.     

一类解析函数的联合留数插值

The necessary and sufficient conditions are given for the simultaneous two-sided residue interpolation problem with nodes in the open upper half-plane for the matrix-valued analytic functions. A linear fractional transformation of the set of all solutions to the question is presented in terms of the original data. The method is based on characterizing least common minimal multiples and the reduction of the solution of the problem to the construction of a rational matrix function which serves as the coefficient, matrix in the linear fractional transformation.     

进化泛函网络多维函数逼近理论及学习算法

提出了一种用于多维函数逼近的进化策略修正泛函网络基函数系数的新算法,并给出了其算法学习过程.利用进化策略的自适应性来确定基函数前的系数,改进了泛函网络的参数通过解方程组来得到这一传统方法.仿真结果表明,这种新的逼近算法简单可行,能够逼近给定的函数到预先给定的精度,具有较快的收敛速度和良好的逼近性能.     

Indefinite integrals of quotients of special functions

A new method is presented for deriving indefinite integrals involving quotients of special functions. The method combines an integration formula given previously with the recursion relations obeyed by the function. Some additional results are presented using an elementary method, here called reciprocation, which can also be used in combination with the new method to obtain additional quotient integrals. Sample results are given here for Bessel functions, Airy functions, associated Legendre functions and the three complete elliptic integrals. All results given have been numerically checked with Mathematica.     

Zur minimierung konvexer subdifferenzierbarer funktionen Über dem R n

A minimization method is described for convex subdifferentiable functions and the convergence proof is given. The method is based on an extension of the subdifferential in such a way that this point to set map is continuous. Different methods follow for a special choice of the used norm and the used extension of the subdifferential. For certain classes of functions the method is explained in detail and corresponding realisations of the extensions of the subdiffential are given.     

An algorithm for the interpolation of functions using quintic splines

A method is described for the interpolation of N arbitrarily given data points using fifth degree polynomial spline functions. The interpolating spline is built from a set of basis functions belonging to the fifth degree smooth Hermite space. The resulting algebraic system is symmetric and bloc-tridiagonal. Its solution is calculated using a direct inversion method, namely a block-gaussian elimination without pivoting. Various boundary conditions are provided for independently at each end point. The stability of the algorithm is examined and some examples are given of experimental convergence rates for the interpolation of elementary analytical functions. A listing is given of the two FORTRAN subroutines INSPL5 and SPLIN5 which form the algorithm.     

Proximal Methods in View of Interior-Point Strategies

This paper deals with regularized penalty-barrier methods for convex programming problems. In the spirit of an iterative proximal regularization approach, an interior-point method is constructed, in which at each step a strongly convex function has to be minimized and the prox-term can be scaled by a variable scaling factor. The convergence of the method is studied for an axiomatically given class of barrier functions. According to the results, a wide class of barrier functions (in particular, logarithmic and exponential functions) can be applied to design special algorithms. For the method with a logarithmic barrier, the rate of convergence is investigated and assumptions that ensure linear convergence are given.     

一类不定积分的巧解

讨论一类分母为多项式二次幂的有理分式的特殊积分法,得到积分公式,并加以推广．新方法有别于将有理分式化为部分分式之和的常用方法．     

Indefinite integrals of products of special functions

A method is given for deriving indefinite integrals involving squares and other products of functions which are solutions of second-order linear differential equations. Several variations of the method are presented, which applies directly to functions which obey homogeneous differential equations. However, functions which obey inhomogeneous equations can be incorporated into the products and examples are given of integrals involving products of Bessel functions combined with Lommel, Anger and Weber functions. Many new integrals are derived for a selection of special functions, including Bessel functions, associated Legendre functions, and elliptic integrals. A number of integrals of products of Gauss hypergeometric functions are also presented, which seem to be the first integrals of this type. All results presented have been numerically checked with Mathematica.     

Euler求和公式的一种推广和应用

将只适用于有限区间上具有连续微商的函数的Eu ler求和公式推广到一般的连续函数,并应用此公式推出对于满足L ipsch itz条件的函数普通数值积分的梯形法、矩形法与S im pson法.     

m值逻辑函数的谱分解式及广义Bent函数的递归构造

本文用概率方法得到ｍ值逻辑函数Ｃｈｒｅｓｔｅｎｓｏｎ循环谱的分解式,据此考察了ｍ值广义Ｂｅｎｔ函数一些新的性质,给出了递归构造ｍ（ｍ≠２ｍｏｄ４）值广义Ｂｅｎｔ函数的一般方法．     

区间有限元方法及其在抗滑稳定性分析中的应用

通过区间值函数和实值函数的关系探讨了区间相关性导致的区间扩张的问题,给出了保证区间计算获得足够精度的计算方法;提出了基于单元的子区间摄动有限元计算方法,并给出了提高计算效率的一些方法和获得较好计算精度时的子区间数目的近似计算公式．结合工程实例,基于单元的子区间有限元方法和抗滑稳定性分析方法给出了稳定性的区间范围,为更合理地估计和评价结构的抗滑稳定性提供一定的依据．