A1 Vertaisarvioitu alkuperäisartikkeli tieteellisessä lehdessä
Determining the signal dimension in second order source separation
Tekijät: Virta Joni, Nordhausen Klaus
Kustantaja: STATISTICA SINICA
Julkaisuvuosi: 2021
Lehti: Statistica Sinica
Tietokannassa oleva lehden nimi: STATISTICA SINICA
Lehden akronyymi: STAT SINICA
Vuosikerta: 31
Numero: 1
Aloitussivu: 135
Lopetussivu: 156
Sivujen määrä: 22
ISSN: 1017-0405
eISSN: 1996-8507
DOI: https://doi.org/10.5705/ss.202018.0347
Verkko-osoite: http://www3.stat.sinica.edu.tw/statistica/j31n1/J31N106/J31N106.html
Rinnakkaistallenteen osoite: https://research.utu.fi/converis/portal/detail/Publication/52801750
Despite being an important topic in practice, estimating the number of non-noise components in blind source separation has received little attention in the literature. Recently, two bootstrap-based techniques for estimating the dimension were proposed; however, although very efficient, they suffer from long computation times as a result of the resampling. We approach the problem from a large-sample viewpoint, and develop an asymptotic test and a corresponding consistent estimate for the true dimension. Our test statistic based on second-order temporal information has a very simple limiting distribution under the null hypothesis, and requires no parameters to estimate. Comparisons with resampling-based estimates show that the asymptotic test provides comparable error rates, with significantly faster computation times. Lastly, we illustrate the method by applying it to sound recording data.
Avainsanat:
chi-square distribution, second order blind identification, second order stationarity, white noise
Ladattava julkaisu This is an electronic reprint of the original article. |  |
