基于SDL的通信软件维护模型SMM

软件维护是软件生存周期的一个重要且花费很大的阶段，维护工作的自动化是软件行业十分迫切的需要。本文提出了一个基于ＩＴＵ－ＴＳＤＬ语言的通信软件维护模型ＳＭＭ。在此模型中，软件维护被分成三个部分：建立面向维护的数据库，制定维护规范和基于功能转换的自动维护。该模型将有助于软件维护支撑环境的建立     

一种基于树形结构显示关联数据的设计

论述了在程序设计过程中 ,使用树形控件、SQL 语句、临时表等多种手段 ,达到多个关联数据库的数据由一个可视化树形结构控件显示的方法和技巧     

B—ISDN宽带UNI信令点到多点配置的实现

本文根据ＩＴＵ－Ｔ最新的Ｑ．２９７１协议，以及笔者所从事的实际课题，提出一整套Ｂ－ＩＳＤＮ第三层ＵＮＩ信令的软件实现策略，其特点是能同时满足用户对点到点以及点到多点广播这两种通信方式的要求，而且可以动态配置。     

基于模糊聚类的语音识别

指出模糊聚类方法影响语间识别的正确率 ,提出用基于分解构造的模糊聚类方法设立语音模式的参考向量 ,说明该方法能提高语章识别的正确率。     

Modeling Language Evolution

We describe a model for the evolution of the languages used by the agents of a society. Our main result proves convergence of these languages to a common one under certain conditions. A few special cases are elaborated in more depth.     

Dependency distance: A new perspective on syntactic patterns in natural languages

Dependency distance, measured by the linear distance between two syntactically related words in a sentence, is generally held as an important index of memory burden and an indicator of syntactic difficulty. Since this constraint of memory is common for all human beings, there may well be a universal preference for dependency distance minimization (DDM) for the sake of reducing memory burden. This human-driven language universal is supported by big data analyses of various corpora that consistently report shorter overall dependency distance in natural languages than in artificial random languages and long-tailed distributions featuring a majority of short dependencies and a minority of long ones. Human languages, as complex systems, seem to have evolved to come up with diverse syntactic patterns under the universal pressure for dependency distance minimization. However, there always exist a small number of long-distance dependencies in natural languages, which may reflect some other biological or functional constraints. Language system may adapt itself to these sporadic long-distance dependencies. It is these universal constraints that have shaped such a rich diversity of syntactic patterns in human languages.     

Towards a Computational Comparative Neuroprimatology: Framing the language-ready brain

We make the case for developing a Computational Comparative Neuroprimatology to inform the analysis of the function and evolution of the human brain.First, we update the mirror system hypothesis on the evolution of the language-ready brain by (i) modeling action and action recognition and opportunistic scheduling of macaque brains to hypothesize the nature of the last common ancestor of macaque and human (LCA-m); and then we (ii) introduce dynamic brain modeling to show how apes could acquire gesture through ontogenetic ritualization, hypothesizing the nature of evolution from LCA-m to the last common ancestor of chimpanzee and human (LCA-c). We then (iii) hypothesize the role of imitation, pantomime, protosign and protospeech in biological and cultural evolution from LCA-c to Homo sapiens with a language-ready brain.Second, we suggest how cultural evolution in Homo sapiens led from protolanguages to full languages with grammar and compositional semantics.Third, we assess the similarities and differences between the dorsal and ventral streams in audition and vision as the basis for presenting and comparing two models of language processing in the human brain: A model of (i) the auditory dorsal and ventral streams in sentence comprehension; and (ii) the visual dorsal and ventral streams in defining “what language is about” in both production and perception of utterances related to visual scenes provide the basis for (iii) a first step towards a synthesis and a look at challenges for further research.     

JPEG2000中位平面编码的VLSI结构设计

位平面编码用于对量化的离散小波变换的码块数据进行编码.通过对位平面编码算法的分析和C语言验证,给出了位平面编码的四种基本编码操作和三个编码通道具体的VLSI结构实现.对位平面编码器的VLSI结构进行了仿真和综合,在图像验证系统上用逻辑分析仪实际测量的结果与仿真结果一致.该位平面编码器可在50 MHz的主频下,完成32×32码块数据的编码.所设计的位平面编码器已经作为单独的IP核应用于目前正在开发的JPEG2000图像编码芯片中.     

Behavioral and computational aspects of language and its acquisition

One of the greatest challenges facing the cognitive sciences is to explain what it means to know a language, and how the knowledge of language is acquired. The dominant approach to this challenge within linguistics has been to seek an efficient characterization of the wealth of documented structural properties of language in terms of a compact generative grammar—ideally, the minimal necessary set of innate, universal, exception-less, highly abstract rules that jointly generate all and only the observed phenomena and are common to all human languages. We review developmental, behavioral, and computational evidence that seems to favor an alternative view of language, according to which linguistic structures are generated by a large, open set of constructions of varying degrees of abstraction and complexity, which embody both form and meaning and are acquired through socially situated experience in a given language community, by probabilistic learning algorithms that resemble those at work in other cognitive modalities.