Fractional programming and characterization of some vertices of the feasible region

This paper considers a problem of nonlinear programming in which the objective function is the ratio of two linear functions and the constraints define a bounded and connected feasible region. Using a coordinate transformation, this problem is transformed into a simpler one, whose geometric interpretation is of particular significance. The transformation leads to a characterization of some special vertices of the feasible region from both the theoretical and operational points of view.     

一类求解线性约束非线性规划问题的可行方向法

Wilson,Han和Powell提出的序列二次规划方法(简称SQP方法)是求解非线性规划问题的一个著名方法,这种方法每次迭代的搜索方向是通过求解一个二次规划子问题得到的,本文受[1]启发,得到二次规划子问题的一个近似解,进而给出了一类求解线性约束非线性规划问题的可行方向法,在约束集合满足正则性的条件下,证明了该算法对五种常用线性搜索方法具有全局收敛性。     

Extended convergence results for the method of multipliers for nonstrictly binding inequality constraints

In this paper, we extend the classical convergence and rate of convergence results for the method of multipliers for equality constrained problems to general inequality constrained problems, without assuming the strict complementarity hypothesis at the local optimal solution. Instead, we consider an alternative second-order sufficient condition for a strict local minimum, which coincides with the standard one in the case of strict complementary slackness. As a consequence, new stopping rules are derived in order to guarantee a local linear rate of convergence for the method, even if the current Lagrangian is only asymptotically minimized in this more general setting. These extended results allow us to broaden the scope of applicability of the method of multipliers, in order to cover all those problems admitting loosely binding constraints at some optimal solution. This fact is not meaningless, since in practice this kind of problem seems to be more the rule rather than the exception.In proving the different results, we follow the classical primaldual approach to the method of multipliers, considering the approximate minimizers for the original augmented Lagrangian as the exact solutions for some adequate approximate augmented Lagrangian. In particular, we prove a general uniform continuity property concerning both their primal and their dual optimal solution set maps, a property that could be useful beyond the scope of this paper. This approach leads to very simple proofs of the preliminary results and to a straight-forward proof of the main results.The author gratefully acknowledges the referees for their helpful comments and remarks. This research was supported by FONDECYT (Fondo Nacional de Desarrollo Científico y Technológico de Chile).     

具连续分布滞量的非线性中立型抛物偏泛函微分方程的振动性

考虑一类具连续分布滞量的非线性中立型抛物偏泛函微分方程解的振动性,借助Green定理和时滞微分不等式获得了这类方程在Robin,Dirichlet边值条件下所有解振动的若干充分条件.     

The uv-Decomposition on a Class of D.C. Functions and Optimality Conditions

In this paper,the UV-theory and P-differential calculus are employed to study second-order ex-pansion of a class of D.C.functions and minimization problems.Under certain conditions,some properties ofthe U-Lagrangian,the second-order expansion of this class of functions along some trajectories are formulated.Some first and second order optimality conditions for the class of D.C.optimization problems are given.     

BRD96N光调制吸收增强现象的实验研究

通过光谱响应特性实验和记录／读出图像实验，研究了基因变异型细菌视紫红质（BR_D96N）分子膜对单色光的光调制特性.发现BR_D96N分子膜在550nm—600nm范围内对调制光有吸收增强的现象，且对此范围内不同波长的单色光其调制程度有差异.利用曲线拟和方法发现550nm—600nm吸收增强的变化过程分为快过程和慢过程，其对应的时间常数分别为30s和5min.利用强度调制器的吸收强度与图像灰度之间的关系，分析了560nm—600nm范围内出现图像反转的实验现象. 关键词： 细菌视紫红质D96N分子膜 光谱响应 吸收增强现象 图像反转现象     

基于重复测量数据的Poisson回归模型的偏大离差的Score检验

Poisson回归模型广泛应用于分析计数型数据 ,Dean&Lawless(1989)和Dean(1992 )讨论了非重复测量得到的计数型数据的偏大离差存在性的检验问题 .本文分别利用随机系数模型和对数非线性模型讨论了基于重复测量得到的计数型数据的偏大离差的检验问题 ,得到了检验的score统计量 .     

PDT光敏剂HA在不同液相体系下的光谱特性研究

为了对候选光敏剂竹红菌甲素(HA)进行改性并保持其优异的敏化特性,对HA的光谱特性和激发态性质作了进一步的指认。系统研究了HA在不同液相体系下的吸收和荧光光谱,对指认HA的光谱和电子跃迁的机制提出了新的依据,结果表明,吸收带I产生于π-π*跃迁,吸收带Ⅱ和Ⅲ产生于P-π共轭所导致的L→aπ跃迁的电子振动结构;荧光发射带I和Ⅱ是产生于同一跃迁机制S1(L,aπ)→S0的正常荧光的振动结构。     

Estimating Invariant Probability Densities for Dynamical Systems

Knowing a probability density (ideally, an invariant density) for the trajectories of a dynamical system allows many significant estimates to be made, from the well-known dynamical invariants such as Lyapunov exponents and mutual information to conditional probabilities which are potentially more suitable for prediction than the single number produced by most predictors. Densities on typical attractors have properties, such as singularity with respect to Lebesgue measure, which make standard density estimators less useful than one would hope. In this paper we present a new method of estimating densities which can smooth in a way that tends to preserve fractal structure down to some level, and that also maintains invariance. We demonstrate with applications to real and artificial data.