从判断到识别的定性映射模型与模糊人工神经元  

Qualitative Mapping Model from Judgment to Recognition and Fuzzy Artificial Neuron

作　　者：冯嘉礼[1] 

机构地区：[1]上海海事大学信息工程学院 计算机系,上海200135

出　　处：《模式识别与人工智能》2006年第1期35-46,共12页Pattern Recognition and Artificial Intelligence

基　　金：上海高校科技发展基金(No.01G04)

摘　　要：将基于属性量-质特征转化的性质命题判断抽象为一个以定性基准为参量的动态定性映射,给出定性基准分别为一个区间、区间向量和 n 维超平行体网格的定义,讨论加权 w 对定性基准的几何意义,定性映射和人工神经元的关系,以及(性质判断的)定性映射转化为(模式)识别映射的机制和条件.指出.加权 w 的实质是对定性基准中的 n 维超平行体实施一个旋转变换.因人工神经元可看作是对 n 维超平行体的一个面实施加权 w 内积旋转变换后的形式,故是(加权 w 内积变换)定性映射的一个特例.当定性基准中 n 维超平行体的所有边长都趋近于零时,以(近)零边长的 n 维超平行体为基准的定性映射转化为一个向量的判断或搜索映射,并可对任一可转化为一个向量的模式进行识别.此外,本文还提出了属性量-质转化程度函数的概念和一种导致定性基准边界模糊化的机制,指出,若用某个模糊化的转化程度函数代替定性映射进行判断和识别,则得到一种模糊判断和识别,并以一系列实例证实了定性映射和转化程度函数方法的实用性.It is shown that a judgment of property （proposition） based on the conversion of a quantity of a attribute a（o） x into a property p（x,o） of a（o） , whose judging result or the truth value of property varies according to its qualitative criterion [α,β] , can be extracted as a dynamic Qualitative Mapping τp （x, [α,β]） whose parameter is criterion [α,β]. Several QM definitions are respectively given whose qualitative criteria are a interval , a vector of intervals and a grid of n - dimension parallelepiped. The geometric mean that a weight w acting on the qualitative criterion [α,β], the relation between a qualitative mapping and an artificial neuron, the mechanism and the condition that a qualitative mapping for judging truth value of property converted into a pattern recognition mapping are respectively discussed. Furthermore, the degree function that a quantity of an attribute converted into a quality or a property and a mechanism fuzzized the boundary of qualitative criterion are presented too. And it＇s shown that if qualitative mapping is substituted by a fuzzized conversion degree function respectively the judgment and recognition would be fuzzy. And a series of examples to test the validity of qualitative mapping and conversion degree function are given

关 键 词：性质命题判断 定性映射 ω_内积变换 转化程度函数 人工神经元 模糊隶属度函数 模式识别 

分 类 号：TP183[自动化与计算机技术—控制理论与控制工程]