一种基于循环小波累积量的谐波恢复方法

循环统计量是乘性和加性噪声中谐波恢复问题的主要分析工具之一。本文在其基础上提出了一种新的理论与方法——基于循环小波累积量的谐波恢复方法。首先,提出了循环小波累积量的定义。然后,建立了基于一阶、二阶、三阶循环小波累积量的谐波分量的频率和相位的估计方法。在此基础上,采用了一种可调参数的小波,通过调节其参数来改善传统方法中频率分辨率低的缺陷。最后给出了模拟实验结果。     

Macroscopic non-equilibrium thermodynamics in dynamic calorimetry

What is really measured in dynamic calorimetric experiments is still an open question. This paper is devoted to this question, which can be usefully envisaged by means of macroscopic non-equilibrium thermodynamics. From the pioneer work of De Donder on chemical reactions and with other authors along the 20th century, the question is tackled under an historical point of view. A special attention is paid about the notions of frequency dependent complex heat capacity and entropy production due to irreversible processes occurring during an experiment. This phenomenological approach based on thermodynamics, not widely spread in the literature of calorimetry, could open significant perspectives on the study of macro-systems undergoing physico-chemical transformations probed by dynamic calorimetry.     

Frame Wavelets with Compact Supports for L^2（R^n）

The construction of frame wavelets with compact supports is a meaningful problem in wavelet analysis. In particular, it is a hard work to construct the frame wavelets with explicit analytic forms. For a given n × n real expansive matrix A, the frame-sets with respect to A are a family of sets in R^n. Based on the frame-sets, a class of high-dimensional frame wavelets with analytic forms are constructed, which can be non-bandlimited, or even compactly supported. As an application, the construction is illustrated by several examples, in which some new frame wavelets with compact supports are constructed. Moreover, since the main result of this paper is about general dilation matrices, in the examples we present a family of frame wavelets associated with some non-integer dilation matrices that is meaningful in computational geometry.     

基于小波变换及布朗分形模型的纹理分割

在研究小波变换及布朗分形模型的基础上，定义了水平分维数，垂直分维数，对角分维数，并将它们作为纹理特征量来实现纹理的分割．实验结果表明，这些特征量能够很好地反映纹理特征，从而分割时不需有关图象中纹理类别的先验信息，较以往方法在准确度和计算复杂程度上都有很大提高．     

一类时变需求且存货影响销售率的EOQ模型

从实际背景出发,在R AM P型需求和存货影响销售率条件下,讨论了一类以缺货开始的变质性物品的EOQ模型.给出了模型的求解方案及单位时间内平均利润最大化的两个充分条件,并用数值算例进行了验证.     

Global Optimal Image Reconstruction from Blurred Noisy Data by a Bayesian Approach

In this paper, a procedure is presented which allows the optimal reconstruction of images from blurred noisy data. The procedure relies on a general Bayesian approach, which makes proper use of all the available information. Special attention is devoted to the informative content of the edges; thus, a preprocessing phase is included, with the aim of estimating the jump sizes in the gray level. The optimization phase follows; existence and uniqueness of the solution is secured. The procedure is tested against simple simulated data and real data.     

WAVELET TRANSFORM IN FRACTAL IMAGE ENCODING

This paper presents some results of the relation between wavelet transform and fractal transform. The wavelet transform of the attractor of fractal transform posseses translational and scale invariance. So we speed the fractal image encoding by testing the invariance of the wavelet transform appropriate for image encoding. The classfication scheme of range blocks by wavelet transform is given in this paper.     

Markovian network processes: Congestion-dependent routing and processing

A Markovian network process describes the movement of discrete units among a set of nodes that process the units. There is considerable knowledge of such networks, often called queueing networks, in which the nodes operate independently and the routes of the units are independent. The focus of this study, in contrast, is on networks with dependent nodes and routings. Examples of dependencies are parallel processing across several nodes, blocking of transitions because of capacity constraints on nodes, alternate routing of units to avoid congestion, and accelerating or decelerating the processing rate at a node depending on downstream congestion. We introduce a general network process representing the numbers of units at the nodes and derive its equilibrium distribution. This distribution takes the form of a product of functions of vectors in which the arguments of the functions satisfy an interchangeability property. This new type of distribution may apply to other multi-variate processes as well. A basic idea in our approach is a linking of certain micro-level balance properties of the network routing to the processing rates at the nodes. The link is via routing-balance partitions of nodes that are inherent in any network. A byproduct of this approach is a general characterization of blocking of transitions without the restriction that the process is reversible, which had been a standard assumption. We also give necessary and sufficient conditions under which a unit moving in the network sees a time average for the unmoved units (called the MUSTA property). Finally, we discuss when certain flows between nodes in an open network are Poisson processes.This research was sponsored in part by Air Force Office of Scientific Research contract 84-0367.     

离散小波变换-遗传算法-交互检验法用于近红外光谱数据的高倍压缩与变量筛选

用遗传算法(GA)与交互检验(CV)相结合建立了一种用于对近红外光谱(NIR)数据及其离散小波变换(DWT)系数进行变量筛选的方法，并应用于烟草样品中总挥发碱和总氮的同时测定。结果表明：NIR数据经DWT压缩为原始大小的3．3％时基本没有光谱信息的丢失；有效的变量筛选可以极大地减少模型中的变量个数，降低模型的复杂程度，改善预测的准确度。