<bold>Improving Simplified Fuzzy ARTMAP Performance Using Genetic Algorithm for Brain Fingerprint Classification</bold>

被引：0
|
作者：
Palaniappan, Ramaswamy [1 ]
Krishnan, Shankar M. [2 ]
Eswaran, Chikkanan [3 ]
机构：
[1] Univ Essex, Dept Comp Sci, Colchester CO4 3SQ, Essex, England
[2] Nanyang Technol Univ, Biomed Engn Res Ctr, Singapore 639798, Singapore
[3] Multimedia Univ, Fac Informat Technol, Cyberjaya, Malaysia
来源：
2006 INTERNATIONAL CONFERENCE ON ADVANCED COMPUTING AND COMMUNICATIONS, VOLS 1 AND 2 | 2007年
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D O I：
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中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
A genetic algorithm is proposed for ordering the input patterns during training for Simplified Fuzzy ARTMAP (SFA) classifier to improve the individual identification classification performance using brain fingerprints. The results indicate improved classification performance as compared to the existing methods for pattern ordering, namely voting strategy and min-max. As the ordering method is general, it could be used with any dataset to obtain improved classification performance when SFA is used.
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页码：319 / +
页数：2
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