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一种吸引分岔知识同模型及其应用实例
引用本文:周昌乐.一种吸引分岔知识同模型及其应用实例[J].软件学报,1996,7(8):505-512.
作者姓名:周昌乐
作者单位:杭州大学计算机科学系,杭州,210028; 北京大学视觉与听觉国家重点实验室,北京,100871
基金项目:本文研究得到浙江省自然科学基金资助.
摘    要:本文基于非线性动力学,特别是托姆的形态发生学思想,针对视觉学习,给出了一种吸引分岔知识网模型,用于解决知识表示和获取问题.通过引入皮亚杰发生认识论中的概念,模型拥有的学习功能包括强化、同化、顺应、聚合、分裂和遗忘;这样就给出了一个学习视觉知识的完整方法.3个应用系统的结果表明,该模型及其学习方法,对于解决实际问题,是有效和适用的.

关 键 词:知识表示    知识获取    学习方法    视觉计算模型    吸引分岔网  
修稿时间:1995/6/23 0:00:00

A MODEL OF THE ATTRACTING-BIFURCATING NETS AND ITS APPLICATION
Zhou Changle.A MODEL OF THE ATTRACTING-BIFURCATING NETS AND ITS APPLICATION[J].Journal of Software,1996,7(8):505-512.
Authors:Zhou Changle
Affiliation:Zhou Changle(Department Of Computer Science Hangzhon University Hangzhou 310028)(Audio and Video National Laboratory Beijing University Beijing 100871)
Abstract:Based on the idea of the nonlinear dynamics,especially the Thom's Morphogenesis,a knowledge model,called attracting-bifurcating net,is advanced to solve the problem of knowledge representation and acquisition for visual learning in this paper.By introducing the Piaget's concepts in genetic epistemology,the model possesses seven main functions which include consolidatation,assimilation,reunion,accommodation,segmentation and forgetting, thus having given out a completed method for learning visual knowledge.The results three application systems show that the model arid its learning method are effective and adaptable to solve visual problems.
Keywords:Knowledge representation  knowledge acquisition  learning method  visual computation model  attraction-bifuracting net
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