收入分配不公平程度测度方法综述

文章针对我国学者研究收入分配时使用分配不公平测度方法比较单一的实际情况,在利用国际上公开发表的有关收入分配不公平程度测度方面的论文、工作报告和专著研究的基础上,首先阐述了有关判断收入分配不公平程度测定指数优良的公理性原则;然后对最常用收入分配不公平程度测度方法按照指数性质分成三大类共十小类,并对各指数的特点、数据要求和适用范围进行了分别阐述。从而避免了采用单个指数研究可能出现的偏差,让研究成果更加客观地、真实地反映收入分配状况和解决收入分配中存在的实际问题。

基于稀疏表示的车用带钢表面图像信息修复

针对当前车用带钢表面图像信息修复所用时间较长,修复效果较差的问题,提出基于稀疏表示的车用带钢表面图像信息修复方法.根据像元点之间在车用带钢表面图像中存在的空间相关信息,结合像元点的灰度分布信息,采用二维直方图建立离散测度矩阵,获得车用带钢表面图像中需要修复的目标区域和背景区域.在稀疏表示原理的基础上构建稀疏修复模型,在车用带钢表面图像的目标区域和背景区域中对受损区域进行修复,能够有效获取车用带钢表面缺陷图像信息,实现车用带钢表面图像信息的修复.实验结果表明,所提方法对车用带钢表面图像信息修复的峰值信噪比较高、均方根误差较小,表明该方法的信息修复效果较好,且修复耗时较短,修复效率高.

一类信道分布的分解

信道在通信系统的一般模型中占有重要的地位。信道分布作为概率和可测函数都与信号的取值集合和信号取值的时间集合有着密切的关系。利用测度论的技巧,在形式上将信道分布分解为四部分,每一部分可以看作信号由某种的输入空间到相同或不同输出空间的信源,这种分解有助于对信源的其他性质和函数空间上算子性质的讨论。

基于图像复杂度的改进Tsallis熵图像阈值分割

Tsallis熵图像阈值分割具有算法简单、应用范围广泛等优点。Tsallis熵算法随着维数的增加使得算法复杂度增大、实时性下降。为了保证算法的分割效果并提高效率,提出基于图像复杂度的Tsallis熵阈值分割算法。通过计算图像复杂度缩小灰度值的遍历范围,并将二维Tsallis熵进行降维处理,引入类内离散测度函数设置新的目标函数,通过对标准测试图像进行验证,以区域间对比度GC作为评价函数,在与一维、二维Tsallis熵算法进行主观与客观效果对比后,发现该算法实时性与分割效果较好。

Discrete-time Markov-based dynamic control approach for compressed sampling

To solve the problem that the signal sparsity level is time-varying and not known as a priori in most cases,a signal sparsity level prediction and optimal sampling rate determination scheme is proposed.The discrete-time Markov chain is used to model the signal sparsity level and analyze the transition between different states.According to the current state,the signal sparsity level state in the next sampling period and its probability are predicted.Furthermore,based on the prediction results,a dynamic control approach is proposed to find out the optimal sampling rate with the aim of maximizing the expected reward which considers both the energy consumption and the recovery accuracy.The proposed approach can balance the tradeoff between the energy consumption and the recovery accuracy.Simulation results show that the proposed dynamic control approach can significantly improve the sampling performance compared with the existing approach.

关于信号滤波中的频率逼近

该文研究信号滤波中的频率逼近问题。结合N-过程和加权因子的方法构造一个新的离散测度,讨论此测度的弱*收敛性。由此测度提供了一个内积形式的定义产生的正交多项式序列-Szeg正交多项式序列。由该多项式序列的零点的性质导出滤波中的未知频率的近似形式,并给出逼近度估计。同时对频率分析问题中的多项式的次数与临界点的个数之间的关系作了一些探讨。

Bottleneck Prediction Method Based on Improved Adaptive Network-based Fuzzy Inference System (ANFIS) in Semiconductor Manufacturing System

Semiconductor manufacturing (SM) system is one of the most complicated hybrid processes involved continuously variable dynamical systems and discrete event dynamical systems. The optimization and scheduling of semiconductor fabrication has long been a hot research direction in automation. Bottleneck is the key factor to a SM system, which seriously influences the throughput rate, cycle time, time-delivery rate, etc. Efficient prediction for the bottleneck of a SM system provides the best support for the consequent scheduling. Because categorical data (product types, releasing strategies) and numerical data (work in process, processing time, utilization rate, buffer length, etc.) have significant effect on bottleneck, an improved adaptive network-based fuzzy inference system (ANFIS) was adopted in this study to predict bottleneck since conventional neural network-based methods accommodate only numerical inputs. In this improved ANFIS, the contribution of categorical inputs to firing strength is reflected through a transformation matrix. In order to tackle high-dimensional inputs, reduce the number of fuzzy rules and obtain high prediction accuracy, a fuzzy c-means method combining binary tree linear division method was applied to identify the initial structure of fuzzy inference system. According to the experimental results, the main-bottleneck and sub-bottleneck of SM system can be predicted accurately with the proposed method.

Predictability of Functional Diversity Depends on the Number of Traits

Analysis of functional diversity, based on plant traits and community structure, provides a promising approach for exploration of the adaptive strategies of plants and the relationship between plant traits and ecosystem functioning. However, it is unclear how the number of plant traits included influences functional diversity, and whether or not there are quantitatively dependent traits. This information is fundamental to the correct use of functional diversity metrics. Here, we measured 34 traits of 366 plant species in nine forests from the tropical to boreal zones in China. These traits were used to calculate seven functional diversity metrics: functional richness(functional attribute diversity(FAD), modified FAD(MFAD), convex hull hypervolume(FRic)), functional evenness(FEve), and functional divergence(functional divergence(FDiv), functional dispersion(FDis), quadratic entropy(Rao Q)). Functional richness metrics increased with an increase in trait number, whereas the relationships between the trait divergence indexes(FDiv and FDis) and trait number were inconsistent. Four of the seven functional diversity indexes(FAD, MFAD, FRic, and RaoQ) were comparable with those in previous studies, showing predictable trends with a change in trait number. We verified our hypothesis that the number of traits strongly influences functional diversity. The relationships between these predictable functional diversity metrics and the number of traits facilitated the development of a standard protocol to enhance comparability across different studies. These findings can support integration of functional diversity index data from different studies at the site to the regional scale, and they focus attention on the influence of quantitative selection of traits on functional diversity analysis.

Stochastic Systems Arising from Markov Modulated Empirical Measures

This work is devoted to stochastic systems arising from empirical measures of random sequences(termed primary sequences) that are modulated by another Markov chain. The Markov chain is used to model random discrete events that are not represented in the primary sequences. One novel feature is that in lieu of the usual scaling in empirical measure sequences, the authors consider scaling in both space and time, which leads to new limit results. Under broad conditions, it is shown that a scaled sequence of the empirical measure converges weakly to a number of Brownian bridges modulated by a continuous-time Markov chain. Ramifications and special cases are also considered.

A New Grey Model Based on Optimizing the Grey Derivative and the Background Value at the Same Time

Based on both white response and connotation expression are geometric progression in the most primitive grey differential equation of GM（1,1）x（k） （k）＋ ax（1） （k） = b, this paper begins with generation of the time response .function＇s grey derivative at discrete points. Through derivative＇s definition, establishing a new GM（1,1） by optimizing grey derivative and background value. Then, getting the best coefficient c by introducing criterion function and it has proved that the new expression has the whitened exponent law coincident property and the whitened coefficient coincident property in theory. Finally, some examples show the new model has higher prediction precision.