《诗经》中的鱼文化

《诗经》中出现鱼字和鱼名的地方约有三十余处,涉及的鱼名有鲂、鳢、鲔等十二种;《诗经》中咏鱼诗篇的表现手法有实叙、比拟、象征等多种,也就是古人常说的"赋、比、兴"。并推断出《诗经》时代的捕鱼方法,有竿钓、网捕、笼捕、设池围捕等。文章最后一节,归纳出鱼在《诗经》时代人们生活中具有用于祭礼、烹制佳肴,表示兴盛,作为象征,取以饰物等多方面的作用。     

Fuzzy格上的Urysohn度量化定理

当Ｌ是Ｆｕｚｚｙ格时,证明了一个ＣⅡ拓扑分子格（Ｌ,η）可点式ｐ．度量化当且仅当其是正则的;可点式度量化当且仅当其是正则Ｔ１的．     

Analysis of clustered spatially correlated binary data using autologistic model and Bayesian method with an application to dental caries of 3–5-year-old children

The autologistic model, first introduced by Besag, is a popular tool for analyzing binary data in spatial lattices. However, no investigation was found to consider modeling of binary data clustered in uncorrelated lattices. Owing to spatial dependency of responses, the exact likelihood estimation of parameters is not possible. For circumventing this difficulty, many studies have been designed to approximate the likelihood and the related partition function of the model. So, the traditional and Bayesian estimation methods based on the likelihood function are often time-consuming and require heavy computations and recursive techniques. Some investigators have introduced and implemented data augmentation and latent variable model to reduce computational complications in parameter estimation. In this work, the spatially correlated binary data distributed in uncorrelated lattices were modeled using autologistic regression, a Bayesian inference was developed with contribution of data augmentation and the proposed models were applied to caries experiences of deciduous dents.     

完全分配格上p．q．度量的刻划

给出了完全分配格上ｐ．ｑ．度量的纯距离函数式刻划与远域映射族式刻划，从而使其更直观且便于应用．     

Determinants of (generalised) Catalan numbers

We show that recent determinant evaluations involving Catalan numbers and generalisations thereof have most convenient explanations by combining the Lindström–Gessel–Viennot theorem on non-intersecting lattice paths with a simple determinant lemma from Krattenthaler (1990). This approach leads also naturally to extensions and generalisations.     

Riordan matrices and higher-dimensional lattice walks

An algebraic combinatorial method is used to count higher-dimensional lattice walks in Z^m${\mathbb{Z}}^m$ that are of length n ending at height k. As a consequence of using the method, Sands’ two-dimensional lattice walk counting problem is generalized to higher dimensions. In addition to Sands’ problem, another subclass of higher-dimensional lattice walks is also counted. Catalan type solutions are obtained and the first moments of the walks are computed. The first moments are then used to compute the average heights of the walks. Asymptotic estimates are also given.     

一般信息系统的PoClustering与概念格

传统聚类方法生成的子集,一般来说都是不相交的.而严格的不相交分类结构,不能充分表现象本体这样的事物间丰富的类关系.在基因本体中,类与子类既不是简单的树也不是格结构,而是一个有向非循环图,其任何子女都可能有多个父结点.PoClustering是相异数据的一种无损聚类方法,概念格则反映了数据的对象和属性的对应关系.采用了PoClustering方法,在保持尽量多的信息的前提下建立一般数据集(信息系统)的属性确定下的概念化分类,讨论了它的算法,从概念格的角度研究了这种类的结构特征.     

COVARIANCE MODELS FOR LATTICE DATA

Given observations on an m × n lattice, approximate maximum likelihood estimates are derived for a family of models including direct covariance, spatial moving average, conditional autoregressive and simultaneous autoregressive models. The approach involves expressing the (approximate) covariance matrix of the observed variables in terms of a linear combination of neighbour relationship matrices, raised to a power. The structure is such that the eigenvectors of the covariance matrix are independent of the parameters of interest. This result leads to a simple Fisher scoring type algorithm for estimating the parameters. The ideas are illustrated by fitting models to some remotely sensed data.     

Subsampling Variance Estimation for Non-stationary Spatial Lattice Data

ABSTRACT.  Most proposed subsampling and resampling methods in the literature assume stationary data. In many empirical applications, however, the hypothesis of stationarity can easily be rejected. In this paper, we demonstrate that moment and variance estimators based on the subsampling methodology can also be employed for different types of non-stationarity data. Consistency of estimators are demonstrated under mild moment and mixing conditions. Rates of convergence are provided, giving guidance for the appropriate choice of subshape size. Results from a small simulation study on finite-sample properties are also reported.     

基于四叉树结构的小波格型矢量量化

基于格型矢量量化克服了传统矢量量化计算和存储复杂度高的缺点,提出了一种新型四叉树结构的小波格型矢量量化算法。对小波变换系数进行视觉加权,以感知的均方误差准则取代传统均方误差。改进零树编码方法,并按照小波系数的四叉树结构和其方向性来组织矢量,对重要系数作格型矢量量化。从而较好地综合利用了小波系数在空间和频域的能量集中特性。仿真实验证明,该方法具有速度快,存储量小的优点,与文献中其他算法相比,具有较高的编码效率。