Power-efficient neural network with artificial dendrites

• Published in: Nature nanotechnology Vol. 15; no. 9; pp. 776 - 782
• Main Authors: Li, Xinyi, Tang, Jianshi, Zhang, Qingtian, Gao, Bin, Yang, J. Joshua, Song, Sen, Wu, Wei, Zhang, Wenqiang, Yao, Peng, Deng, Ning, Deng, Lei, Xie, Yuan, Qian, He, Wu, Huaqiang
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 01.09.2020; Nature Publishing Group
• Subjects: 639/166/987; 639/925/927/1007; Animals; Application specific integrated circuits; Artificial Cells; Artificial neural networks; Background noise; Central processing units; Chemistry and Materials Science; Computer simulation; CPUs; Databases, Factual; Dendrites; Dendrites - physiology; Electronics; Energy efficiency; Equipment Design; Image Processing, Computer-Assisted; Integrated circuits; Materials Science; Memristors; Mice; Models, Neurological; Multilayers; Nanotechnology; Nanotechnology and Microengineering; Nervous system; Neural networks; Neural Networks, Computer; Neurons - physiology; Oxygen - chemistry; Power consumption; Power management; Signal processing; Synapses; Task complexity

In the nervous system, dendrites, branches of neurons that transmit signals between synapses and soma, play a critical role in processing functions, such as nonlinear integration of postsynaptic signals. The lack of these critical functions in artificial neural networks compromises their performance...