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MULTI-DOMAIN FEATURE EXTRACTION FOR SMALL EVENT-RELATED POTENTIALS THROUGH NONNEGATIVE MULTI-WAY ARRAY DECOMPOSITION FROM LOW DENSE ARRAY EEG

FENGYU CONG

Department of Mathematical Information Technology, University of Jyväskylä, Finland

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ANH-HUY PHAN

Laboratory for Advanced Brain Signal Processing, RIKEN Brain Science Institute, Japan

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PIIA ASTIKAINEN

Department of Psychology, University of Jyväskylä, Finland

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QIBIN ZHAO

Laboratory for Advanced Brain Signal Processing, RIKEN Brain Science Institute, Japan

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QIANG WU

School of Information Science and Engineering, Shandong University, Jinan, Shandong, China

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JARI K. HIETANEN

Human Information Processing laboratory, School of Social Sciences and Humanities, University of Tampere, Finland

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TAPANI RISTANIEMI

Department of Mathematical Information Technology, University of Jyväskylä, Finland

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, and

ANDRZEJ CICHOCKI

Laboratory for Advanced Brain Signal Processing, RIKEN Brain Science Institute, Japan

Systems Research Institute in Polish Academy of Science, Warsaw, Poland

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https://doi.org/10.1142/S0129065713500068Cited by:63 (Source: Crossref)

Abstract

Non-negative Canonical Polyadic decomposition (NCPD) and non-negative Tucker decomposition (NTD) were compared for extracting the multi-domain feature of visual mismatch negativity (vMMN), a small event-related potential (ERP), for the cognitive research. Since signal-to-noise ratio in vMMN is low, NTD outperformed NCPD. Moreover, we proposed an approach to select the multi-domain feature of an ERP among all extracted features and discussed determination of numbers of extracted components in NCPD and NTD regarding the ERP context.

Keywords:

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