AR 型非线性时间序列模型的稳定性分析

在工程中,振幅依赖指数自回归模型、门限自回归模型和多项式自回归模型等一类具有ＡＲ型的非线性时间序列模型具有广泛的应用,为此给出了ＡＲ型非线性时间序列模型的稳定性条件及极限环存在条件,并对一些特殊模型进行了讨论。     

网络拓扑模型述评

网络拓扑模型广泛地应用于网络研究中。简单概述了网络拓扑模型的相关度量及常见的网络拓扑模型,重点综述了从真实网络中总结的幂法则及相应的模型,并描述了最近发现的Rich-Club现象及其模型。最后剖析了该领域当前存在的问题,展望了今后的发展方向。     

Studies in the theory of algebraic models of programs with procedures

Algebraic models of programs with procedures extend algebraic models of programs that are free of procedures (simple models of programs). A specific feature of both types of models is that they are built for some formalization of software programs. Models of programs are intended for studying functional equivalence of formalized programs and constructing wide sets of equivalent transformations of programs. Two basic problems in the theory of algebraic models of programs are the equivalence problem and the problem of building complete systems of equivalent transformations. An increasing interest in models of programs with procedures is due to the abundance of results obtained for simple models of programs. The most suitable model of programs with procedures is a gateway model. A remarkable feature of these models is that every such model is induced by some simple model of programs. This paper gives a survey of the latest results obtained for gateway models of programs.     

On a class of algebraic models of programs of practical interest

Algebraic program models are designed for the study of the semantic properties of programs on models—program schemas. The design concepts of these models are presented, and a class of models is considered that approximate real sequential programs. Algorithms are constructed that recognize the equivalence of program schemas in models of a given class with practically acceptable complexity. The validity of these algorithms for constructing equivalent transformations (ETs) of program schemas is established.     

城市微观交通流模型综述

车辆跟驰模型和换车道模型是微观交通流模型研究的基础。对GM模型、线性模型、安全距离模型、AP模型、模糊推理模型和神经网络的车辆跟驰模型进行了详细的评述,并提出了现有的车辆跟驰模型存在的问题。并且对判断性换车道模型和强制性换车道模型进行了详细地论述,同时对其进行了评价。     

A new perspective for discrete-time models of a continuous-timesystem

Various discrete-time models of a continuous-time system are given an interpretation in terms of the system structures and the hold device. This concept provides a novel perspective of various discrete-time models and a simple way to understand the relationships which exist among those models, but which are not easily visualized without the proposed interpretation. This interpretation of discrete-time models also allows the creation of new types of models. Tables of discrete-time models, including the newly developed ones, are provided     

自然语言处理中的模型

本文简单介绍了自然语言处理发展的现状,讨论了自然语言处理模型,将其分为三大类：分析模型、统计模型及混合模型。具体介绍了分析模型原理及存在的问题,重点讨论了各种统计模型的特点及局限性,最后简单介绍了混合模型,并指出目前自然语言处理技术中存在的问题。     

On definable concepts of rough set models

In various generalized rough set models, definable concepts are used to approximate other concepts. Based on a unified abstract rough set theory, this paper investigates the mathematical structure of the set of definable concepts in several generalized rough set models such as relation based models, covering based models, and fuzzy based models. It is shown that there exist two kinds of interesting structures for the set of definable concepts, which are often used in rough set models: the complementary structure and the equational structure. In addition, relations between different rough set models are discussed.     

Development life cycle of computer networks: the executable modelapproach

An approach is proposed for extending the use of design models to the implementation and operational phases of the network development life cycle. A conceptual approach is offered for using executable models in the day-to-day operation of computer networks. Several strategies are given for integrating models into different development tasks. It is shown why these strategies are feasible. Characteristics of executable models that differ from those of traditional models are identified along with new technologies that reduce the cost of implementing and using executable models     

A comparison of descriptive models of a single spike train by information-geometric measure

In examining spike trains, different models are used to describe their structure. The different models often seem quite similar, but because they are cast in different formalisms, it is often difficult to compare their predictions. Here we use the information-geometric measure, an orthogonal coordinate representation of point processes, to express different models of stochastic point processes in a common coordinate system. Within such a framework, it becomes straightforward to visualize higher-order correlations of different models and thereby assess the differences between models. We apply the information-geometric measure to compare two similar but not identical models of neuronal spike trains: the inhomogeneous Markov and the mixture of Poisson models. It is shown that they differ in the second- and higher-order interaction terms. In the mixture of Poisson model, the second- and higher-order interactions are of comparable magnitude within each order, whereas in the inhomogeneous Markov model, they have alternating signs over different orders. This provides guidance about what measurements would effectively separate the two models. As newer models are proposed, they also can be compared to these models using information geometry.