一款具有0.2$\mu$J/类基于多路复用器神经网络的闭环脑机接口SoC
信号处理
2024-01-09 v1
摘要
本工作展示了首款已流片的电生理-光遗传闭环双向脑机接口（CL-BBMI）片上系统（SoC），具备电神经信号记录、片上睡眠分期和光遗传刺激功能。首次提出了基于静态分配查表解决方案的多路复用器（MUXnet），用于无乘法器神经网络处理器。在睡眠分期任务中，实现了82.4%的先进平均准确率，能耗仅为0.2J/类。
引用
@article{arxiv.2401.03396,
title = {A Closed-loop Brain-Machine Interface SoC Featuring a 0.2$\mu$J/class Multiplexer Based Neural Network},
author = {Chao Zhang and Yongxiang Guo and Dawid Sheng and Zhixiong Ma and Chao Sun and Yuwei Zhang and Wenxin Zhao and Fenyan Zhang and Tongfei Wang and Xing Sheng and Milin Zhang},
journal= {arXiv preprint arXiv:2401.03396},
year = {2024}
}
备注
2 pages, 6 figures. Accepted by IEEE Custom Integrated Circuits Conference (CICC) 2024. The codes for the MUXnet (constructing neural networks using multiplexers instead of multipliers) will be open-sourced after the Journal version of this work is accepted