Complex- Valued Neural Networks - Recent Progress and Future Directions

被引:0
作者
Hirose, Akira [1 ]
机构
[1] Univ Tokyo, Dept Elect Engn & Informat Syst, Bunkyo Ku, 7-3-1 Hongo, Tokyo 1138656, Japan
来源
NEURAL INFORMATION PROCESSING (ICONIP 2014), PT I | 2014年 / 8834卷
关键词
WALLED-LTSA ARRAY; FREQUENCY-DOMAIN; LAND CLASSIFICATION; LEARNING ALGORITHM; PLASTIC LANDMINES; INTERFEROMETRY; VISUALIZATION; RESTORATION; RESOLUTION; SYSTEM;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This invited paper presents and discusses the recent progress, present and prospective applications, and the future directions of complex-valued neural networks (CVNNs) including hypercomplex-valued neural networks (HVNNs).
引用
收藏
页码:223 / 230
页数:8
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