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Ladle Estimator for Time Series Signal Dimension
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en
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5
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2018 IEEE Statistical Signal Processing Workshop, SSP 2018, pp. 428-432
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.
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Nordhausen, K & Virta, J 2018, Ladle Estimator for Time Series Signal Dimension. in 2018 IEEE Statistical Signal Processing Workshop, SSP 2018., 8450695, IEEE, pp. 428-432, IEEE Statistical Signal Processing Workshop, Freiburg im Breisgau, Germany, 10/06/2018. https://doi.org/10.1109/SSP.2018.8450695