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信息熵通过系统变化规律的研究
引用本文:王宏禹,连兵.信息熵通过系统变化规律的研究[J].大连理工大学学报,1995,35(4):544-548.
作者姓名:王宏禹  连兵
作者单位:大连理工大学信息技术研究所
基金项目:国家自然科学基金资助项目
摘    要:对孤立热力系统中的不可逆过程,热力系统熵自发不可逆地增加;而对自发进行的物理变化过程,物理场熵是减小的。迄今,信息系统中信息熵的变化规律尚不十分明确。对此进行研究,得出结论:带限平稳正态随机信号通过因果最小相位线性系统后,熵可增加或减小,可用线性逆系统使熵可逆变化;平稳非正态独立同分布随机信号通过因果非最小相位线性系统后,熵恒增加,并趋近平稳正态信号,使熵趋于最大。原线性系统不能使熵可逆变化,亦不

关 键 词:  偏序  随机信号  累积量  信息熵

Study of variational law of information entropy passing through systems
Wang Hongyu,Lian Bing.Study of variational law of information entropy passing through systems[J].Journal of Dalian University of Technology,1995,35(4):544-548.
Authors:Wang Hongyu  Lian Bing
Abstract:For irreversible processes in an isolated thermodynamic system,the thermodynamicentropy increases spontaneously and irreversibly,while for spontaneous physical processes,physical field entropy decreases. Up to now,the variational law of information entropy ininformation systems is not quite clear yet.This is studied and the following conclusions aregiven:After a frequency-banded stationary normal random signal passes causal minimum phaselinear systems,its entropy may increase or decrease and linear inverse systems can be used toinversely change entropy.After a stationary non-normal i. i.d.random signal passes causal non-minimum phase linear systems,it tends towards stationary normal signal,while its entropyconstantly increases and tends towards maximum. The primary system cannot inversely changeentropy, nor can any linear inverse system. Only by adding minus entropy,or equivalentlypassing through a nonlinear system can entropy decrease to minimum.
Keywords:entropy(automation)  partial order  random signals/cumulant
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