The squared symmetric FastICA estimator
Miettinen, J., Nordhausen, K., Oja, H., Taskinen, S., & Virta, J. (2017). The squared symmetric FastICA estimator. Signal Processing, 131(February), 402-411. https://doi.org/10.1016/j.sigpro.2016.08.028
Published inSignal Processing
© 2016 Elsevier B.V. This is a final draft version of an article whose final and definitive form has been published by Elsevier. Published in this repository with the kind permission of the publisher.
In this paper we study the theoretical properties of the deflation-based FastICA method, the original symmetric FastICA method, and a modified symmetric FastICA method, here called the squared symmetric FastICA. This modification is obtained by replacing the absolute values in the FastICA objective function by their squares. In the deflation-based case this replacement has no effect on the estimate since the maximization problem stays the same. However, in the symmetric case we obtain a different estimate which has been mentioned in the literature, but its theoretical properties have not been studied at all. In the paper we review the classic deflation-based and symmetric FastICA approaches and contrast these with the squared symmetric version of FastICA in a unified way. We find the estimating equations and derive the asymptotical properties of the squared symmetric FastICA estimator with an arbitrary choice of nonlinearity. This allows the main contribution of the paper, i.e., efficiency comparison of the estimates in a wide variety of situations using asymptotic variances of the unmixing matrix estimates. ...
PublisherElsevier BV; European Association for Signal Processing
Publication in research information system
MetadataShow full item record
Showing items with similar title or keywords.
Snowball ICA : A Model Order Free Independent Component Analysis Strategy for Functional Magnetic Resonance Imaging Data Hu, Guoqiang; Waters, Abigail B.; Aslan, Serdar; Frederick, Blaise; Cong, Fengyu; Nickerson, Lisa D. (Frontiers Media, 2020)In independent component analysis (ICA), the selection of model order (i.e., number of components to be extracted) has crucial effects on functional magnetic resonance imaging (fMRI) brain network analysis. Model order ...
Event-related potentials to unattended changes in facial expressions: detection of regularity violations or encoding of emotions? Astikainen, Piia; Cong, Fengyu; Ristaniemi, Tapani; Hietanen, Jari K. (Frontiers, 2013)Visual mismatch negativity (vMMN), a component in event-related potentials (ERPs), can be elicited when rarely presented “deviant” facial expressions violate regularity formed by repeated “standard” faces. vMMN is observed ...
Miettinen, Jari; Nordhausen, Klaus; Taskinen, Sara (Foundation for Open Access Statistics, 2017)Blind source separation (BSS) is a well-known signal processing tool which is used to solve practical data analysis problems in various fields of science. In BSS, we assume that the observed data consists of linear ...
Examining stability of independent component analysis based on coefficient and component matrices for voxel-based morphometry of structural magnetic resonance imaging Zhang, Qing; Hu, Guoqiang; Tian, Lili; Ristaniemi, Tapani; Wang, Huili; Chen, Hongjun; Wu, Jianlin; Cong, Fengyu (Springer Netherlands, 2018)Independent component analysis (ICA) on group-level voxel-based morphometry (VBM) produces the coefficient matrix and the component matrix. The former contains variability among multiple subjects for further statistical ...
Tsatsishvili, Valeri; Cong, Fengyu; Ristaniemi, Tapani; Toiviainen, Petri; Alluri, Vinoo; Brattico, Elvira; Nandi, Asoke (IEEE, 2014)In contrast to block and event-related designs for fMRI experiments, it becomes much more difficult to extract events of interest in the complex continuous stimulus for finding corresponding blood-oxygen-level ...