An exact, linear solution to the problem of imaging through turbulence

We show how, in principle, to solve the ‘blind deconvolution' problem. This is in the context of the problem of imaging through atmospheric turbulence. The approach is digital but not iterative, and requires as input data but two short-exposure intensity images, without the need for reference point sources. By taking the Fourier transform of each image and dividing, a set of linear equations is generated whose unknowns are sampled values of the two random point spread functions that degraded the images. An oversampling by 50% in Fourier space equalizes the number of unknowns and independent equations. With some prior knowledge of spread function support, and in the absence of added noise of image detection, the inverted equations give exact solutions. The two observed images are then inverse filtered to reconstruct the object.     

The skew elliptical distributions and their quadratic forms

In this paper, a family of the skew elliptical distributions is defined and investigated. Some basic properties, such as stochastic representation, marginal and conditional distributions, distribution under linear transformations, moments and moment generating function are derived. The joint distribution of several quadratic forms is obtained. An example is given to show that the distributions of some statistics as the functions of the quadratic forms can be derived for various applications.     

An inequality for the group chromatic number of a graph

We give an inequality for the group chromatic number of a graph as an extension of Brooks’ Theorem. Moreover, we obtain a structural theorem for graphs satisfying the equality and discuss applications of the theorem.     

保险赔付中的最优对冲策略

本文对带有付费过程$A_t$的保险公司在金融市场$(S_t,Q_t,B_t)$上通过购买股票$S_t$、兑换外币$Q_t$以及购买无风险资产$B_t$的投资过程而采取的最优投资策略, 使保险公司所面临的风险最小进行探讨. 利用Galtchouk-Kunita-Watanabe分解定理将风险表达式重新表达, 从而找到保险公司所能采取的风险最小的最优对冲策略. 文中举出一个具有现实性意义的例子将文章的重要结论加以应用, 使本文更具有应用价值.     

On splittable colorings of graphs and hypergraphs

The notion of a split coloring of a complete graph was introduced by Erd?s and Gyárfás [ 7 ] as a generalization of split graphs. In this work, we offer an alternate interpretation by comparing such a coloring to the classical Ramsey coloring problem via a two‐round game played against an adversary. We show that the techniques used and bounds obtained on the extremal (r,m)‐split coloring problem of [ 7 ] are closer in nature to the Turán theory of graphs rather than Ramsey theory. We extend the notion of these colorings to hypergraphs and provide bounds and some exact results. © 2002 Wiley Periodicals, Inc. J Graph Theory 40: 226–237, 2002     

Convex optimization and lagrange multipliers

The duality theorem of linear programming is used to prove several results on convex optimization. This is done without using separating hyerplane theorems.This work was supported in part by a grant from Investors in Business Education.     

Canonical Pattern Ramsey Numbers

A color pattern is a graph whose edges have been partitioned into color classes. A family of color patterns is a Ramsey family provided there is some sufficiently large integer N such that in any edge coloring of the complete graph K_N there is an (isomorphic) copy of at least one of the patterns from . The smallest such N is the Ramsey number of the family . The classical Canonical Ramsey theorem of Erds and Rado asserts that the family of color patterns is a Ramsey family if it consists of monochromatic, rainbow (totally multicolored) and lexically colored complete graphs. In this paper we treat the asymmetric case by studying the Ramsey number of families containing a rainbow triangle, a lexically colored complete graph and a fixed arbitrary monochromatic graph. In particular we give asymptotically tight bounds for the Ramsey number of a family consisting of rainbow and monochromatic triangle and a lexically colored K_N. Among others, we prove some canonical Ramsey results for cycles.     

A polynomial of degree four not satisfying Rolle’s theorem in the unit ball of <Emphasis Type="Italic">l</Emphasis><Subscript>2</Subscript>

We give an example of a fourth degree polynomial which does not satisfy Rolles Theorem in the unit ball of l ₂.The author has been partially supported by MCyT and FEDER Project BFM2002-01423.     

Some multivariate inequalities with applications

Summary Let <InlineEquation ID=IE"1"><EquationSource Format="TEX"><![CDATA[<InlineEquation ID=IE"2"><EquationSource Format="TEX"><![CDATA[<InlineEquation ID=IE"3"><EquationSource Format="TEX"><![CDATA[<InlineEquation ID=IE"4"><EquationSource Format="TEX"><![CDATA[<InlineEquation ID=IE"5"><EquationSource Format="TEX"><![CDATA[<InlineEquation ID=IE"6"><EquationSource Format="TEX"><![CDATA[<InlineEquation ID=IE"7"><EquationSource Format="TEX"><![CDATA[<InlineEquation ID=IE"8"><EquationSource Format="TEX"><![CDATA[<InlineEquation ID=IE"9"><EquationSource Format="TEX"><![CDATA[$]]></EquationSource></InlineEquation>]]></EquationSource></InlineEquation>]]></EquationSource></InlineEquation>]]></EquationSource></InlineEquation>]]></EquationSource></InlineEquation>]]></EquationSource></InlineEquation>]]></EquationSource></InlineEquation>]]></EquationSource></InlineEquation>]]></EquationSource></InlineEquation>{\cal {X}}_{n} =(X_1,\ldots,X_n)$ be a random vector. Suppose that the random variables $(X_i)_{1\leq i\leq n}$ are stationary and fulfill a suitable dependence criterion. Let $f$ be a real valued function defined on $\mathbbm{R}^n$ having some regular properties. Let ${\cal {Y}}_{n}$ be a random vector, independent of ${\cal {X}}_{n}$, having independent and identically distributed components. We control $\left|\mathbbm{E}(f({\cal {X}}_{n}))-\mathbbm{E} (f({\cal {Y}}_{n}))\right|$. Suitable choices of the function $f$ yield, under minimal conditions, to rates of convergence in the central limit theorem, to some moment inequalities or to bounds useful for Poisson approximation. The proofs are derived from multivariate extensions of Taylor's formula and of the Lindeberg decomposition. In the univariate case and in the mixing setting the method is due to Rio (1995).     

D-Optimal designs for weighted polynomial regression—A functional approach

This paper is concerned with the problem of computing approximateD-optimal design for polynomial regression with analytic weight function on a interval [m ₀-a,m ₀+a]. It is shown that the structure of the optimal design depends ona and weight function. Moreover, the optimal support points and weights are analytic functions ofa ata=0. We make use of a Taylor expansion to provide a recursive procedure for calculating theD-optimal designs.