Exponential distributions on semigroups

Three fundamental characterizations of the standard exponential distribution on [0, ) are the remaining life, memoryless and constant failure properties. Analogs of these properties are studied for distributions on a class of semigroups in which the semigroup operation replaces addition, a compatible partial order replaces the ordinary order, and a left-invariant measure replaces Lebesgue measure. Partial characterizations of exponential distributions on such semigroups are obtained and the semigroup formulation provides new characterizations of certain aging properties studied in reliability-increasing failure rate, new better than used, and increasing failure rate average.     

The diagnonal multivariate natural exponential families and their classification

A natural exponential family (NEF)F in ? ⁿ ,n>1, is said to be diagonal if there existn functions,a ₁,...,a _n , on some intervals of ?, such that the covariance matrixV _F (m) ofF has diagonal (a ₁(m ₁),...,a _n (m _n )), for allm=(m ₁,...,m _n ) in the mean domain ofF. The familyF is also said to be irreducible if it is not the product of two independent NEFs in ? ^k and ? ^n-k , for somek=1,...,n?1. This paper shows that there are only six types of irreducible diagonal NEFs in ? ⁿ , that we call normal, Poisson, multinomial, negative multinomial, gamma, and hybrid. These types, with the exception of the latter two, correspond to distributions well established in the literature. This study is motivated by the following question: IfF is an NEF in ? ⁿ , under what conditions is its projectionp(F) in ? ^k , underp(x ₁,...,x _n )∶=(x ₁,...,x _k ),k=1,...,n?1, still an NEF in ? ^k ? The answer turns out to be rather predictable. It is the case if, and only if, the principalk×k submatrix ofV _F (m ₁,...,m _n ) does not depend on (m _k+1,...,m _n ).     

q-Hypergeometric Series and Macdonald Functions

We derive a duality formula for two-row Macdonald functions by studying their relation with basic hypergeometric functions. We introduce two parameter vertex operators to construct a family of symmetric functions generalizing Hall-Littlewood functions. Their relation with Macdonald functions is governed by a very well-poised q-hypergeometric functions of type ₄₃, for which we obtain linear transformation formulas in terms of the Jacobi theta function and the q-Gamma function. The transformation formulas are then used to give the duality formula and a new formula for two-row Macdonald functions in terms of the vertex operators. The Jack polynomials are also treated accordingly.     

Approximating the zeros of analytic functions by the exclusion algorithm

We give a practical version of the exclusion algorithm for localizing the zeros of an analytic function and in particular of a polynomial in a compact of . We extend the real exclusion algorithm to a Jordan curve and give a method which excludes discs without any zero. The result of this algorithm is a set of discs arbitrarily small which contains the zeros of the analytic function.     

Virial expansion for a polymer with a realistic pair-potential interaction

No modern theory of polymer excluded volume adequately describes the crossover from poor solvent to good solvent conditions; a fundamental difficulty is a singularity in the binary cluster integral. Mayer expansion techniques are applied to a model with a pair interaction between monomers to clarify the distinction between geometric and solvent contributions to excluded volume. Detailed calculations are undertaken for a hard-core potential and a mimic Lennard-Jones potential. The significance of the singularity in the binary cluster integral for calculations in the crossover regime is discussed.     

Schrödinger invariance and strongly anisotropic critical systems

The extension of strongly anisotropic or dynamical scaling to local scale invariance is investigated. For the special case of an anisotropy or dynamical exponent =z=2, the group of local scale transformation considered is the Schrödinger group, which can be obtained as the nonrelativistic limit of the conformal group. The requirement of Schrödinger invariance determines the two-point function in the bulk and reduces the three-point function to a scaling form of a single variable. Scaling forms are also derived for the two-point function close to a free surface which can be either spacelike or timelike. These results are reproduced in several exactly solvable statistical systems, namely the kinetic Ising model with Glauber dynamics, lattice diffusion, Lifshitz points in the spherical model, and critical dynamics of the spherical model with a nonconserved order parameter. For generic values of , evidence from higher-order Lifshitz points in the spherical model and from directed percolation suggests a simple scaling form of the two-point function.     

Probabilistic approach to homoclinic chaos

Three-dimensional systems possessing a homoclinic orbit associated to a saddle focus with eigenvalues ±i, – and giving rise to homoclinic chaos when the Shil'nikov condition < is satisfied are studied. The 2D Poincaré map and its 1D contractions capturing the essential features of the flow are given. At homoclinicity, these 1D maps are found to be piecewise linear. This property allows one to reduce the Frobenius—Perron equation to a master equation whose solution is analytically known. The probabilistic properties such as the time autocorrelation function of the state variablex are explicitly derived.     

一种新的TDCS基函数生成方法及性能分析

针对变换域通信系统基函数生成过程中硬判决门限难以精确设置且判决复杂度高的问题,提出了一种功率谱翻转的基函数生成方法。该方法在对电磁环境采样估计的基础上,利用环境谱翻转来构造基函数幅度谱,省去了传统门限值设置和判决的步骤,从而大大降低了通信系统的运算复杂度;另外,由于没有完全舍弃被干扰的频段,与传统的"0"、"1"硬判决相比,该方法生成的基函数频率组成更加丰富而具有更好的相关特性。仿真结果表明:功率反转的基函数生成方法可以降低系统的运算复杂度,同时提高基函数的相关性能,为TDCS的深入研究提供了新的思路。     

基于未确知数学的网络安全风险评估模型

结合网络安全评价中存在诸多不确定因素的特点,提出一种基于未确知数学理论的网络安全综合评价新方法。分析了网络安全风险的因素,建立了网络安全风险评价因素的指标体系和评价等级空间。在分析网络安全风险因素的基础上,建立了网络安全风险评价因素的指标体系和评价等级空间,将未确知数学的方法运用于网络安全风险的综合评估中,在未确知测度理论的基础上,定义了未确知测度期望、未确知评价等级二值效应量值、综合评价的未确知测度向量、未确知等级二值效应期望和二值效应方差等新的未确知数学概念。在新的未确知概念的基础上,建立了网络安全风险综合评估的未确知数学模型。并用实例对该模型进行了应用,评价结果用一个未确知有理数来表示更符合实际。实例表明该方法计算简单科学有效,为网络安全综合评价提供了一种新途径。     

神经网络校正的EKF在高超声速目标跟踪中的应用

针对临近空间高超声速目标高度非线性、强耦合、高机动、时变参数、和独特气动特性等特点,综合运用军事运筹学理论与方法、系统建模技术、神经网络技术以及计算机仿真等,提出基于神经网络校正的扩展卡尔曼滤波(EKF)算法,并在高超声速目标跟踪中进行了应用研究。采取神经网络的学习能力来克服卡尔曼滤波发散问题,通过卡尔曼滤波后加一级误差处理环节使滤波收敛。仿真结果表明:该算法在目标发生较大机动时仍能保持较高的跟踪精度。