Ladle Estimator for Time Series Signal Dimension

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

Researchers

  • Klaus Nordhausen
  • Joni Virta

Research units

  • Vienna University of Technology

Abstract

We consider a second order source separation model where a set of latent signals is internally mixed with several channels of noise and the goal is to estimate the number of signals. For the purpose we extend the ladle estimator which has been so far considered only for iid methods such as PCA, CCA or FOBI. Using time series bootstrapping methods ladle estima-tors based on AMUSE and SOBI are presented and a simulation study demonstrates that especially SOBI works well if the time series are sufficiently long.

Details

Original languageEnglish
Title of host publication2018 IEEE Statistical Signal Processing Workshop, SSP 2018
Publication statusPublished - 29 Aug 2018
MoE publication typeA4 Article in a conference publication
EventIEEE Statistical Signal Processing Workshop - Freiburg im Breisgau, Germany
Duration: 10 Jun 201813 Jun 2018
Conference number: 20

Workshop

WorkshopIEEE Statistical Signal Processing Workshop
Abbreviated titleSSP
CountryGermany
CityFreiburg im Breisgau
Period10/06/201813/06/2018

    Research areas

  • AMUSE, bootstrap, order determination, SOBI

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