互补型自适应滤波器在心磁信号处理中的应用

将心磁信号从干扰噪声中加以提取并有效地消除噪声干扰是心磁信号处理中尤为重要的环节 .从改进算法的角度出发，提出互补型自适应滤波器结构以实现心磁信号的消噪处理.该滤波器针对心磁这类非平稳信号进行设计，有效地解决了常规自适应滤波器应用于心磁信号处理时收敛速度和稳态误差的矛盾.通过仿真实验和心磁实验结果表明，该算法能有效地消除心磁信号的背景噪声和工频干扰噪声.同时该算法也可用于其他非平稳信号的消噪处理. 关键词： 自适应滤波 心磁图 最小均方误差     

Existence and characterization of regions minimizing perimeter under a volume constraint inside Euclidean cones

We study the problem of existence of regions separating a given amount of volume with the least possible perimeter inside a Euclidean cone. Our main result shows that nonexistence for a given volume implies that the isoperimetric profile of the cone coincides with the one of the half-space. This allows us to give some criteria ensuring existence of isoperimetric regions: for instance, local convexity of the cone at some boundary point.

We also characterize which are the stable regions in a convex cone, i.e., second order minima of perimeter under a volume constraint. From this it follows that the isoperimetric regions in a convex cone are the euclidean balls centered at the vertex intersected with the cone.

     

异方差回归中的广义方差比检验

在同方差假设之下,线性模型在回归分析的理论与应用方面起着突出的作用,很受许多研究工作者的青睐.然而,回归模型中同方差性这一标准假设不一定总是成立的.因此我们考虑了用一类基于似残差的方法来检验异方差情形下线性模型拟合观测数据的情况.本文既给出了大量的模拟,又给出了实际数据作为应用的例子.效果都很好.     

On the even power mean of a sum analogous to Dedekind sums

Summary Our purpose is to extend results due to P. Chandra and L. Leindler concerning the order of approximation by means of Fourier series for functions belonging to generalized Lipschitz-classes.     

Direct and inverse estimates for a new family of linear positive operators

In the present paper we introduce a new family of linear positive operators and study some direct and inverse results in simultaneous approximation.     

Balanced contributions for TU games with awards and applications

Calleja et al. [Calleja, P., Borm, P., Hendrickx, R., 2005. Multi-issue allocation situations. European Journal of Operational Research 164, 730–747] introduced multi-issue allocation situations with awards. In this paper, we extend the classical model of cooperative games with transferable utility to the cooperative games with transferable utility and awards. We define a run-to-the-bank rule for cooperative games with transferable utility and awards and characterise it in terms of a property of balanced contributions. We apply our main result to bankruptcy problems and multi-issue allocation situations with awards.     

Global and exploding solutions in a model of self-gravitating systems

We study asymptotic properties of solutions to an extension to arbitrary dimensions of the astrophysical model proposed by Chavanis et al. to explain phenomena of gravitational collapse in clouds of self-gravitating particles. In particular, we show that in the two-dimensional case the solutions can be continued to global ones, while in three space dimensions large data of negative energy blow up in a finite time. Relations between isothermal, Streater's energy-transport and the present models are also studied.     

A note on conservation laws for a multiclass service queueing system with setup times

This paper derives a conservation law for mean waiting times in a single-server multi-class service queueing system (M ^X/G/1 type queue) with setup times which may be dependent on multiple customer classes and its arrival batch size by using the work decomposition property in the queueing system with vacations.     

核内核子－核子非弹散射截面（Ⅰ）

在与平均场、核内核子－核子弹性散射截面以及输运方程相统一的理论框架内推导了核内核子－核子非弹散射截面的解析表达式．其数值结果能很好地重现自由非弹截面的实验值，所计算的有效非弹截面与Ｄｉｒａｃ－Ｂｒｕｅｃｋｎｅｒ的计算结果相一致．     

Improved customer choice predictions using ensemble methods

In this paper various ensemble learning methods from machine learning and statistics are considered and applied to the customer choice modeling problem. The application of ensemble learning usually improves the prediction quality of flexible models like decision trees and thus leads to improved predictions. We give experimental results for two real-life marketing datasets using decision trees, ensemble versions of decision trees and the logistic regression model, which is a standard approach for this problem. The ensemble models are found to improve upon individual decision trees and outperform logistic regression.