title: Autoregressive model in the Lp norm space for EEG analysis.
abstract: The autoregressive (AR) model is widely used in electroencephalogram (EEG) analyses such as waveform fitting, spectrum estimation, and system identification. In real applications, EEGs are inevitably contaminated with unexpected outlier artifacts, and this must be overcome. However, most of the current AR models are based on the L2 norm structure, which exaggerates the outlier effect due to the square property of the L2 norm. In this paper, a novel AR object function is constructed in the Lp (p≤1) norm space with the aim to compress the outlier effects on EEG analysis, and a fast iteration procedure is developed to solve this new AR model. The quantitative evaluation using simulated EEGs with outliers proves that the proposed Lp (p≤1) AR can estimate the AR parameters more robustly than the Yule-Walker, Burg and LS methods, under various simulated outlier conditions. The actual application to the resting EEG recording with ocular artifacts also demonstrates that Lp (p≤1) AR can effectively address the outliers and recover a resting EEG power spectrum that is more consistent with its physiological basis.
authors.affiliation: Key Laboratory for NeuroInformation of the Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China.
authors.forename: Peiyang
authors.initials: P
authors.lastname: Li
authors.affiliation: Key Laboratory for NeuroInformation of the Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China.
authors.forename: Xurui
authors.initials: X
authors.lastname: Wang
authors.affiliation: Key Laboratory for NeuroInformation of the Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China.
authors.forename: Fali
authors.initials: F
authors.lastname: Li
authors.affiliation: Key Laboratory for NeuroInformation of the Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China.
authors.forename: Rui
authors.initials: R
authors.lastname: Zhang
authors.affiliation: Key Laboratory for NeuroInformation of the Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China.
authors.forename: Teng
authors.initials: T
authors.lastname: Ma
authors.affiliation: School of Microelectronics and Solid-State Electronics, University of Electronic Science and Technology of China, Chengdu, China.
authors.forename: Yueheng
authors.initials: Y
authors.lastname: Peng
authors.affiliation: School of Physiology, Southwest University, Chongqing, China.
authors.forename: Xu
authors.initials: X
authors.lastname: Lei
authors.affiliation: School of Bioinformatics, Chongqing university of Posts and Telecommunications, Chongqing, China.
authors.forename: Yin
authors.initials: Y
authors.lastname: Tian
authors.affiliation: Key Laboratory for NeuroInformation of the Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China.
authors.forename: Daqing
authors.initials: D
authors.lastname: Guo
authors.affiliation: Key Laboratory for NeuroInformation of the Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China.
authors.forename: Tiejun
authors.initials: T
authors.lastname: Liu
authors.affiliation: Key Laboratory for NeuroInformation of the Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China.
authors.forename: Dezhong
authors.initials: D
authors.lastname: Yao
authors.affiliation: Key Laboratory for NeuroInformation of the Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China. Electronic address: xupeng@uestc.edu.cn.
authors.forename: Peng
authors.initials: P
authors.lastname: Xu
mesh_terms: D000465:Algorithms; D016477:Artifacts; D001767:Blinking / Q000502:physiology; D001921:Brain / Q000502:physiology; D003198:Computer Simulation; D004569:Electroencephalography / Q000379:methods*; D006801:Humans; D008297:Male; D008959:Models, Neurological; D012146:Rest; D012815:Signal Processing, Computer-Assisted
keywords: Autoregressive model; EEG; Lp norm; Power spectrum