电子学报 ›› 2018, Vol. 46 ›› Issue (3): 748-754.DOI: 10.3969/j.issn.0372-2112.2018.03.033

• 学术论文 • 上一篇    下一篇

压缩感知的重叠神经元峰电位信号分类

杨凯, 吴海锋, 曾玉   

  1. 云南民族大学电气信息工程学院, 云南昆明 650500
  • 收稿日期:2016-12-14 修回日期:2017-02-18 出版日期:2018-03-25
  • 通讯作者: 吴海锋
  • 作者简介:杨凯,男,1991年生于湖北麻城.现为云南民族大学硕士研究生.主要研究方向为神经网络与机器学习.E-mail:250145249@qq.com;曾玉,女,1981年生于安徽无为.现为云南民族大学讲师.主要研究方向为神经网络与机器学习.E-mail:yv.zeng@gmail.com
  • 基金资助:
    国家自然科学基金(No.61262091); 云南省第十七批中青年学术和技术带头人资助项目(No.2014HB019); 云南省高校科技创新团队支持计划资助; 云南民族大学研究生创新基金项目(No.2016YJCXSY11)

Compressive Sensing for Overlapping Neural Spike Sorting

YANG Kai, WU Hai-feng, ZENG Yu   

  1. School of Electrical and Information Technology, Yunnan Minzu University, Kunming, Yunnan 650500, China
  • Received:2016-12-14 Revised:2017-02-18 Online:2018-03-25 Published:2018-03-25

摘要: 随着电生理技术水平的提高,电极可以记录的峰电位信号包含多个神经元峰电位的叠加.本文提出了一种采用压缩感知和最大后验估计的分类算法来解决重叠峰电位分类问题.其中压缩感知算法用于得到稀疏信号,最大后验估计用于搜索出稀疏信号的最优解.在实验中,我们采用仿真和实测的三组数据对本文算法和传统算法进行了测试,实验结果表明,当峰电位波形相似时,相比于k-均值聚类及CBP(Continuous Basis Pursuit)算法,本文算法具有较少的分类错误数.

关键词: 峰电位分类, 重叠的峰电位, 压缩感知, 聚类, 连续基追踪

Abstract: With the development of electrophysiological technology,the spike signals that electrodes record contain multi-neuron overlapped spikes.This paper presents a classification method based on a compressed sensing algorithm and a maximum a posteriori (MAP) estimate to sort the overlapped spikes.The compressed sensing algorithm is used to obtain sparse signals,and the maximum a posteriori estimate is used to search an optimal value in the sparse signals.In experiments,we use one group of simulation data and two groups of measured data to verify the method.The experimental results show that when the spike waveform shapes in the data are similar,the proposed method has fewer sorting errors compared with the existing algorithms,k-means clustering and CBP (Continuous Basis Pursuit).

Key words: spike sorting, overlapping spike, compressive sensing, clustering, continuous basis pursuit

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