Jamalabadi, H. und Gais, S. (2017) Optimizing parameters and algorithms of multivariate pattern classification for hypothesis testing in high-density EEG [cd]. Universitätsbibliothek Tübingen. doi:urn:nbn:de:bsz:21-dspace-782834.
Chicago Manual of Style 17th edition (full note)Jamalabadi, Hamidreza, und Steffen Gais. „Optimizing parameters and algorithms of multivariate pattern classification for hypothesis testing in high-density EEG“. Cd. Universitätsbibliothek Tübingen, [2017?], Universitätsbibliothek Tübingen, [2017?]. https://doi.org/urn:nbn:de:bsz:21-dspace-782834.
American Psychological Association 7th editionJamalabadi, H., & Gais, S. (ca. 2017). Optimizing parameters and algorithms of multivariate pattern classification for hypothesis testing in high-density EEG [Universitätsbibliothek Tübingen; Cd]. https://doi.org/urn:nbn:de:bsz:21-dspace-782834
Modern Language Association 9th editionJamalabadi, H., und S. Gais. Optimizing parameters and algorithms of multivariate pattern classification for hypothesis testing in high-density EEG. cd, Universitätsbibliothek Tübingen, 2017, https://doi.org/urn:nbn:de:bsz:21-dspace-782834.
ISO-690 (author-date, Deutsch)JAMALABADI, Hamidreza und Steffen GAIS, 2017. Optimizing parameters and algorithms of multivariate pattern classification for hypothesis testing in high-density EEG. Tübingen: Universitätsbibliothek Tübingen