A1 Journal article (refereed)
Low-rank approximation based non-negative multi-way array decomposition on event-related potentials (2014)

Cong, F., Zhou, G., Astikainen, P., Zhao, Q., Wu, Q., Nandi, A., Hietanen, J. K., Ristaniemi, T., & Cichocki, A. (2014). Low-rank approximation based non-negative multi-way array decomposition on event-related potentials. International Journal of Neural Systems, 24(8), Article 1440005. https://doi.org/10.1142/S012906571440005X

JYU authors or editors

Publication details

All authors or editorsCong, Fengyu; Zhou, Guoxu; Astikainen, Piia; Zhao, Qibin; Wu, Qiang; Nandi, Asoke; Hietanen, Jari K.; Ristaniemi, Tapani; Cichocki, Andrzej

Journal or seriesInternational Journal of Neural Systems



Publication year2014


Issue number8

Article number1440005

PublisherWorld Scientific

Place of PublicationSingapore

Publication countrySingapore

Publication languageEnglish


Publication open accessOpenly available

Publication channel open accessPartially open access channel

Publication is parallel published (JYX)https://jyx.jyu.fi/handle/123456789/77841


Non-negative tensor factorization (NTF) has been successfully applied to analyze event-related potentials (ERPs), and shown superiority in terms of capturing multi-domain features. However, the time-frequency representation of ERPs by higher-order tensors are usually large-scale, which prevents the popularity of most tensor factorization algorithms. To overcome this issue, we introduce a non-negative canonical polyadic decomposition (NCPD) based on low-rank approximation (LRA) and hierarchical alternating least square (HALS) techniques. We applied NCPD (LRAHALS and benchmark HALS) and CPD to extract multi-domain features of a visual ERP. The features and components extracted by LRAHALS NCPD and HALS NCPD were very similar, but LRAHALS NCPD was 70 times faster than HALS NCPD. Moreover, the desired multi-domain feature of the ERP by NCPD showed a significant group difference (control versus depressed participants) and a difference in emotion processing (fearful versus happy faces). This was more satisfactory than that by CPD, which revealed only a group difference.

Free keywordsEvent-related potential; low-rank approximation; multi-domain feature; non-negative canonical polyadic decomposition; non-negative tensor factorization; tensor decomposition

Contributing organizations

Ministry reportingYes

Reporting Year2014

JUFO rating1

Last updated on 2024-09-05 at 22:46