NA序列广义Jamison型加权和的几乎处处收敛性

本文从随机变量序列广义Ｊａｍｉｓｏｎ型加权和的一个系数指标函数自身性质出发，讨论了广义Ｊａｍｉｓｏｎ型加权和的强稳定性，避免了控制函数的引入， 进一步还得到了更一般的ＮＡ序列广义Ｊａｍｉｓｏｎ型加权和的几乎处处收敛的条件，并将前人的若干结论包含为特例．     

基于Bootstrap的厚尾相依序列持久性变点检验

基于修正方差比率函数给出一种检验厚尾序列持久性变点的统计量.在无变点的假设下得到了统计量的渐近分布.为避免检验渐近分布中的厚尾指数,构造Bootstrap抽样方法来确定渐近分布的经验临界值.数值模拟研究结果说明修正方差比率统计量及Bootstrap抽样方法的有效性.     

基于Hamilton路模型的蛋白质结构预测的研究

提出一种基于Hamilton路模型的新方法研究蛋白质结构预测问题,为使结构匹配序列,把已知蛋白质的3D结构信息转化为一个加权的完全图Kn,则求这个特定空间结构所匹配的氨基酸残基序列问题转化为求Kn图的最小H路问题.用此方法研究了72个单链蛋白质结构,结果表明Kn图的最小H路对应此蛋白质的序列,图的顶点数n与最小H路总长度成正比.     

价格与隐含远期违约概率

如同根据布莱克-斯科尔斯模型从欧式看涨期权市场价格中反求隐含波动率一样,从信用违约互换的价格中提取隐含违约概率在理论上和实践上都存在很多困难.传统的自助法存在很大的缺点,并有可能得出不符合现实的结果.本文采用基于一段时期的条件违约概率的新的优化方法来替代基于自助法的瞬时远期违约概率,该方法有很多优良特性,会得出比传统方法好得多的结论.     

论连通图的可重构性

本文我们利用带权核子图的可重构性证明了连通图是可重构的,从而证明了重构猜想为真.     

Maximal inequality and complete convergences of non-identically distributed negatively associated sequences

A maximal inequality for the partial sum of NA sequence is constructed.By using this inequality the complete convergence rates in the strong laws for a class of dependent random variables for weighted sums are discussed.The results obtained extend the results of Liang(1999, 2000).     

Multiscale Weighted Permutation Entropy Analysis of Schizophrenia Magnetoencephalograms

Schizophrenia is a neuropsychiatric disease that affects the nonlinear dynamics of brain activity. The primary objective of this study was to explore the complexity of magnetoencephalograms (MEG) in patients with schizophrenia. We combined a multiscale method and weighted permutation entropy to characterize MEG signals from 19 schizophrenia patients and 16 healthy controls. When the scale was larger than 42, the MEG signals of schizophrenia patients were significantly more complex than those of healthy controls (p<0.004). The difference in complexity between patients with schizophrenia and the controls was strongest in the frontal and occipital areas (p<0.001), and there was almost no difference in the central area. In addition, the results showed that the dynamic range of MEG complexity is wider in healthy individuals than in people with schizophrenia. Overall, the multiscale weighted permutation entropy method reliably quantified the complexity of MEG from schizophrenia patients, contributing to the development of potential magnetoencephalographic biomarkers for schizophrenia.     

AN EFFICIENT SEQUENTIAL DESIGN FOR SENSITIVITY EXPERIMENTS

In sensitivity experiments, the response is binary and each experimental unit has a critical stimulus level that cannot be observed directly. It is often of interest to estimate extreme quantiles of the distribution of these critical stimulus levels over the tested products. For this purpose a new sequential scheme is proposed with some commonly used models. By using the bootstrap repeated-sampling principle, reasonable prior distributions based on a historic data set are specified. Then, a Bayesian strategy for the sequential procedure is provided and the estimator is given. Further, a high order approximation for such an estimator is explored and its consistency is proven. A simulation study shows that the proposed method gives superior performances over the existing methods.     

Properties of mono-weakly hyponormal 2-variable weighted shifts

In this paper, we study several properties for mono-weakly hyponormal 2-variable weighted shifts. First, we consider propagation phenomena for mono-weakly hyponormal (resp. mono-polynomially hyponormal) 2-variable weighted shifts. Next, we contemplate the mono-weak hyponormality under the Schur product. Finally, we study whether the mono-weak hyponormality is invariant under powers.     

An improved partial SPIHT with classified weighted rate-distortion optimization for interferential multispectral image compression

Based on the property analysis of interferential multispectral images, a novel compression algorithm of partial set partitioning in hierarchical trees (SPIHT) with classified weighted rate-distortion optimization is presented.After wavelet decomposition, partial SPIHT is applied to each zero tree independently by adaptively selecting one of three coding modes according to the probability of the significant coefficients in each bitplane.Meanwhile the interferential multispectral image is partitioned into two kinds of regions in terms of luminous intensity, and the rate-distortion slopes of zero trees are then lifted with classified weights according to their distortion contribution to the constructed spectrum.Finally a global ratedistortion optimization truncation is performed.Compared with the conventional methods, the proposed algorithm not only improves the performance in spatial domain but also reduces the distortion in spectral domain.