DISCRETE PROLATE SPHEROIDAL SEQUENCES FOR COMPRESSIVE SENSING OF EEG SIGNALS

摘要：

Electroencephalography (EEG) is a major tool for clinical diagnosis of neurological diseases and brain research. EEGs are often collected over numerous channels and trials, providing large data sets that require efficient collection and accurate compression. Compressive sensing (CS) emphasizing signal sparseness enables the reconstruction of signals from a small set of measurements, at the expense of computationally complex reconstruction algorithms. In this paper we show that using Discrete Prolate Spheroidal Sequences, rather than sinc functions, it is possible to derive a sampling and reconstruction method which is similar to CS. Assuming non-uniform sampling our procedure can be connected with compressive sensing without complex reconstruction methods.

关键词： Uncertainty principal prolate spheroidal wave functions compressive sensing random sampling

作者: Seda Senay Luis F.Chaparro Rui-Zhen Zhao Robert J.Sclabassi Mingui Sun

作者单位: Dept.of Electrical and Computer Engineering,University of Pittsburgh, Pittsburgh, PA, 15261 USA School of Computer and Information Technology, Beijing Jiaotong University, 100044, CHINA Laboratory for Computational Neuroscience, University of Pittsburgh,Pittsburgh, PA, 15261 USA Dept.of Electrical and Computer Engineering,University of Pittsburgh, Pittsburgh, PA, 15261 USA Labo

会议类型: 国际会议

会议名称: 2010 IEEE 10th International Conference on Signal Processing(第十届信号处理国际会议 ICSP 2010)

会议地点: 北京

会议语种:英文

页码: 54-57

在线出版日期: 2010-08-24（万方平台首次上网日期，不代表论文的发表时间）