@inproceedings{b54bca72a4a446f7bd4ce58ea74096e2,
title = "Study on efficiency of weight-discretized BP neural network algorithm based on memory curves of synaptic transistor",
abstract = "With the development of artificial intelligence, synaptic transistors have become the core devices of neuromorphic computing. Based on the memory characteristic curves of synaptic transistor, this paper studies the effect of symmetry/asymmetry curve models and the non-linearity on the efficiency of weight-discretized BP neural network algorithm. The results show that higher discrete points, asymmetric models and lower non-linearity lead to lower efficiency. This research is of guiding significance to the modeling of artificial neural network algorithm and the development of future hardware neural networks.",
keywords = "Efficiency, Memory curve, Non-linearity, Synaptic transistor, Weight-discretized BP neural network",
author = "Wang, \{Yi Ming\} and Jia Song and Li, \{Guo Peng\} and Sheng Chen and Yu, \{Du Li\} and Li, \{Yu Tao\}",
note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 16th IEEE International Conference on Solid-State and Integrated Circuit Technology, ICSICT 2022 ; Conference date: 25-10-2022 Through 28-10-2022",
year = "2022",
doi = "10.1109/ICSICT55466.2022.9963200",
language = "English",
series = "Proceedings of 2022 IEEE 16th International Conference on Solid-State and Integrated Circuit Technology, ICSICT 2022",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
editor = "Fan Ye and Ting-Ao Tang",
booktitle = "Proceedings of 2022 IEEE 16th International Conference on Solid-State and Integrated Circuit Technology, ICSICT 2022",
address = "United States",
}