Computing with High-Dimensional Vectors

被引：11
|
作者：
Kanerva, Pentti [1 ]
机构：
[1] Univ Calif Berkeley, Redwood Ctr Theoret Neurosci, Berkeley, CA 94720 USA
来源：
IEEE DESIGN & TEST | 2019年 / 36卷 / 03期
关键词：
Computational algebra; Energy-efficiency; Holographic Reduced Representation; Nanotechnology; Parallelism; Robustness;
D O I：
10.1109/MDAT.2018.2890221
中图分类号：
TP3 [计算技术、计算机技术];
学科分类号：
0812 ;
摘要：
Editor's note: The author reviews the principles of high-dimensional (HD) computing as a brain-inspired paradigm, with variables and operations encoded in vectors with high dimensionality (e.g., 10,000). HD computing has been shown to be a robust novel approach with promising applications in language and biosignal processing.
引用
收藏
页码：7 / 14
页数：8
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