摘要: Real world data is rough and intermittent. When applying neural networks to simulate such functions, accuracy is a problem. Higher Order Neural Network (HONN) models have the ability to converge without difficulty. A single model ... 展开
作者 | Jessica Marie Crane Ming Zhang | ||
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文集名称 | Proceedings of The IASTED International Conference on Computational Intelligence | ||
出版年 | 2005 | ||
出版社/出版地 | International Association of Science and Technology for Development (IASTED) / [s.l.] | ||
会议名称 | International Association of Science and Technology for Development International Conference on Computational Intelligence | ||
开始页/总页数 | 7 / 6 | ||
会议日期/会议地点 | 2005 / Calgary | 会议年 | 2005 |
中图分类号 | TP18-53 | ||
关键词 | Data Simulation Data Simulator HONN SINCHONN | ||
馆藏号 | N2009EMST0002562 |