摘要
本文主要探讨信息论跨学科发展的基本问题、理论和方法。通过分析Shannon测度,得出:‘划分’是获取信息的依据和根本方法。利用连续划分由离散信源熵推导连续信源熵。可消除logΔ→∞的矛盾。通过讨论模糊划分,得到划分的信息客观度和信息散失度;定量解决了正确选择‘划分’的问题。针对Shannon信源和划分的缺陷,本文提出了普适划分。从而可以认知信源输出的语法信息和语义识别信息;并且证明:Shannon信息是后者的近似。对先验知识不足的信源,用灰色信源描述。灰熵、灰信息作为熵和信息的估计;并用感知度δ_k定量描述了它们的接近程度,
In this paper, we mainly discuss about the fundamental problems, theary and methods for the interdisciplinary development of information theory. Analysing the shannon measure, it is obtaited that division is the basis and fundamental method of gaining infer mation. By deriving the continuous entropy from the discrete entroPy with continuous division, we can dispel the contradictory of log△→∞. Discussing the fuzzy division,we obtain the degree of information objectivity and the degree of information loss of the division, therefore can select correctly division in numerical guantitiesoln order to Solve the defect of shannon information source and the division, we advance the universal division,, Thereby we can cognize the syntax information and the semanteme recognition information from the output of information source. And it is Proved that shannon information is the approximation of the later. The information source, which lack the priori knowledge, are described as the grey source. The Gray entropy and the Grey information are used as the estimate of the eatropy and the information; and with the degree of Perception their proximaty is measured.
出处
《西北建筑工程学院学报（自然科学版）》
1989年第2期66-78,共13页
Journal of Northwestern Institute of Architectural Engineering
关键词
信息认知
普适划分
语法信息
information cognition,universal division, syntax information, semanteme recognition information, grey information source, degree of perception.
