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题名: Biomimetic pattern recognition theory and its applications
作者: Wang SJ;  Zhao XT
发表日期: 2004
摘要: Biomimetic pattern recogntion (BPR), which is based on "cognition" instead of "classification", is much closer to the function of human being. The basis of BPR is the Principle of homology-continuity (PHC), which means the difference between two samples of the same class must be gradually changed. The aim of BPR is to find an optimal covering in the feature space, which emphasizes the "similarity" among homologous group members, rather than "division" in traditional pattern recognition. Some applications of BPR are surveyed, in which the results of BPR are much better than the results of Support Vector Machine. A novel neuron model, Hyper sausage neuron (HSN), is shown as a kind of covering units in BPR. The mathematical description of HSN is given and the 2-dimensional discriminant boundary of HSN is shown. In two special cases, in which samples are distributed in a line segment and a circle, both the HSN networks and RBF networks are used for covering. The results show that HSN networks act better than RBF networks in generalization, especially for small sample set, which are consonant with the results of the applications of BPR. And a brief explanation of the HSN networks' advantages in covering general distributed samples is also given.
KOS主题词: Pattern perception
刊名: CHINESE JOURNAL OF ELECTRONICS
专题: 中国科学院半导体研究所(2009年前)_期刊论文

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推荐引用方式:
Wang, SJ; Zhao, XT .Biomimetic pattern recognition theory and its applications ,CHINESE JOURNAL OF ELECTRONICS,JUL 2004,13 (3):373-377
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