Affine Poisson structures

We establish a one-to-one correspondence between the set of all equivalence classes of affine Poisson structures (defined on the dual of a finite dimensional Lie algebra) and the set of all equivalence classes of central extensions of the Lie algebra by ℝ. We characterize all the affine Poisson structures defined on the duals of some lower dimensional Lie algebras. It is shown that under a certain condition every Poisson structure locally looks like an affine Poisson structure. As an application, we show the role played by affine Poisson structures in mechanics. Finally, we prove some involution theorems.     

On the robust estimation in poisson processes with periodic intensities

Under some regularity conditions, it is well known that the maximum likelihood estimator (MLE) is asymptotically normal and efficient. However, if the observation is contaminated, the MLE is not always an appropriate estimator. In this paper, we treat M-estimators and study their asymptotic behavior. By choosing estimation equations, robust M-estimators are presented for phase parameters.     

局部Lipschitz条件下的布朗运动和泊松过程混合驱动的正倒向随机微分方程

本文得到在局部Lipschiz条件下的布朗运动和泊松过程混合驱动的倒向随机微分方程的存在唯一性；同时也证明了布朗运动和泊松过程混合驱动的完全藕合的正倒向随机微分方程在局部Lipschitz条件下的解的存在唯一性。     

r-Matrix Structure for a Restricted Flow with Bargmann Constraint

This paper deals with the integrability of a finite-dimensional Hamiltonian system linked with the generalized coupled KdV hierarchy. For this purpose the associated Lax representation is presented after an elementary calculation. It is shown that the Lax representation enjoys a dynamical r-matrix formula instead of a classical one in the Poisson bracket on R^2N. Consequently the resulting system is proved to be completely integrable in view of its r-matrix structure.     

Limits for Szegö polynomials in frequency analysis

We characterize limits for orthogonal Szegö polynomials of fixed degree k, with respect to certain measures on the unit circle which are weakly convergent to a sum of m<k point masses. Such measures arise, for example, as a convolution of point masses with an approximate identity. It is readily seen that the underlying measures in two recently-proposed methods for estimating the m frequencies, θj, of a discrete-time trigonometric signal using Szegö polynomials are of this form. We prove existence of Szegö polynomial limits associated with a general class of weakly convergent measures, and prove that for convolution of point masses with the Poisson kernel, which underlies one of the recently-proposed methods, the limit has as a factor the Szegö polynomial with respect to a related measure, which we specify. Since m of the zeros approach the eiθj, this result uniquely characterizes the limit. A similar result is obtained for measures consisting of point masses with additive absolutely continuous part.     

面向电子商务的应用——基于多Agen t的消费者需求代理系统

首先根据电子商务环境下消费者需求的特点,在对多A gen t技术论述的基础上,建立了基于多A gen t的消费者需求代理系统.接着对系统具体工作流程进行了深入分析:先针对不同消费者建立相应的用户模型,以便为不同消费者提供效用最大化的产品或产品服务的组合,然后采用协商型A gen t,完成网上产品或服务的交易.最后提出了基于遗传算法的协商谈判策略,以提高消费者需求代理系统的协商能力.     

Quality targets in dipstick urinalysis

Point of care testing (POCT) of urine has been practiced for many centuries. It has come particularly into its own in the second half of the 20th century with the development of tablet- and later dipstick-testing systems. Unfortunately, it has become embedded in clinical practice outside the laboratory, missing the development of the quality culture that has developed inside the laboratory. Analysis of the results of a Urine Quality Assurance Programme demonstrate the value and the need for this quality culture.     

Poisson方程Cauchy问题对数型稳定性

本文在ｍ＋１维欧几里得空间中讨论Ｐｏｉｓｓｏｎ方程Ｃａｕｃｈｙ问题解的稳定性，利用Ｔｉｋｈｏｎｏｖ，栾文贵，Ｙａｍａｍｏｔｏ的关于不适定问题的解法获得了解的对数型稳定性估计。     

A multivariate Markov chain model for categorical data sequences and its applications in demand predictions

Markov models are commonly used in modelling many practicalsystems such as telecommunication systems, manufacturing systemsand inventory systems. In this paper we propose a multivariateMarkov chain model for modelling multiple categorical data sequences.We develop efficient estimation methods for the model parameters.We then apply the model and method to demand predictions fora soft-drink company in Hong Kong.