← 返回 JSSC 论文列表JSSC 2023第11期Digital Circuits22nm
An Online-Spike-Sorting IC Using Unsupervised Geometry-Aware OSort Clustering fo
一款用于384通道神经信号处理的在线尖峰排序IC，采用无监督几何感知OSort聚类技术，实现高精度和低功耗。
22nm FDSOI CMOS, 0.0013 mm²/通道, 1.78 µW/通道, 33.9 µs延迟, 97.7%准确率
在线尖峰排序神经信号处理器无监督聚类几何感知OSort低功耗IC
▸中央尖峰检测（CSD）算法减少冗余尖峰对精度的影响
▸峰值一阶和二阶导数极值（FSDE）方法实现鲁棒特征提取
▸几何感知OSort（Geo-OSort）算法平衡聚类阶段的精度与复杂度
Abstract
As neural-recording devices get denser and generate
more data due to ever higher channel counts, on-chip and
online neural signal processor (NSP) becomes crucial to reduce
the data-transmission power and to enable real-time closed-loop
applications with minimum latency. For this purpose, we report
an online spike-sorting integrated circuit (IC) able to process
neural signals from 384 channels with software-comparable
accuracy. By combining three main innovations, our design
drastically improves