一种低功耗尖峰检测与对齐算法

A. Zviagintsev, Y. Perelman, R. Ginosar
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引用次数: 6

摘要

用于信号处理的前端集成电路在涉及大量电极的神经元记录系统中非常有用。在前端检测、校准和排序尖峰数据可减少数据带宽并实现无线通信。如果没有这样的数据减少,就需要将大量数据传输到主机计算机,并且通常需要笨重的电缆,这将限制患者或试验动物。由于供应限制和热量限制,前端处理电路只能耗散有限的功率。介绍了基于积分变换的低复杂度尖峰检测与对齐算法及其体系结构。它们达到了PCA检测器99%的精度,而计算复杂度仅为PCA检测器的0.05%
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Low-Power Spike Detection and Alignment Algorithm
Front-end integrated circuits for signal processing are useful in neuronal recording systems that engage a large number of electrodes. Detecting, alignment, and sorting the spike data at the front-end reduces the data bandwidth and enables wireless communication. Without such data reduction, large data volumes need to be transferred to a host computer and typically heavy cables are required which constrain the patient or test animal. Front-end processing circuits can dissipate only a limited amount of power, due to supply constraints and heat restrictions. Reduced complexity spike detection and alignment algorithm and architecture, based on integral transform, are introduced. They achieve 99% of the precision of a PCA detector, while requiring only 0.05% of the computational complexity
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