| 摘要: |
| ＦＴＡＲＴ（ｆｉｅｌｄｔｈｅｏｒｙ－ｂａｓｅｄＡＲＴ）算法结合了ＡＲＴ（ａｄａｐｔｉｖｅｒｅｓｏｎａｎｃｅｔｈｅｏｒｙ）算法、ＡＲＴＭＡＰ算法、域理论的思想，以样本在实例空间中出现的概率为启发信息修改学习中生成的分类，采用了不同于其它算法的解决样本间的冲突和动态扩大分类区域的方法．本文在对ＦＴＡＲＴ算法的研究的基础上进行了改进，使算法在学习连续函数的映射时更加有效．同时给出了算法的测试结果和对测试结果的分析，测试表明，ＦＴＡＲＴ算法在模式识别和连续函数映射的学习方面具有比较好的性能. |
| 关键词: 神经网络 ARTMAP算法 连续函数映射 |
| DOI： |
| 分类号: |
| 基金项目:国家自然科学基金国家自然科学基金资助. |
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| ANALYSIS AND IMPROVEMENT OF FTART ALGORITHM |
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CHEN Zhaoqian,LI Hongbing,ZHOU Rong,CHEN Shifu
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| Abstract: |
| FTART(field theory—based ART)algorithm combines the theory of ART (adaptive resonance theory)，ARTMAP and field theory．It corrects the generated classi-fication regarding the supposed distribution possibility of examples in the instance space．FTART employes a different conflict resolve process and dynamicly expanding the classifi-cation area．By further studies，the paper improves the algorithm'S ability of learning continuous function mappings．Some benchmark test results and the analysis are also given．They proved that FTART has good performance on pattern recognition and continuous function mapping． |
| Key words: Neural network ARTMAP algorithm continuous function mapping |
