Relating Independent Components to Free-Vibration Modal Responses
Scot McNeill,D.C. Zimmerman +1 more
TLDR
The relationship between independent components and free-vibration modal responses is discussed in this article, where theoretical arguments are presented for responses of undamped systems and arguments are extended to damped responses.Abstract:
In recent literature, attempts have been made to apply Independent Component Analysis (ICA) techniques to the modal identification problem. Paramount to this task is establishing a relationship between the source components realized using the suggested ICA technique and modal responses. In this paper, the relationship between independent components and free-vibration modal responses is discussed. Theoretical arguments are presented for responses of undamped systems and arguments are extended to damped responses.read more
Citations
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A review of output-only structural mode identification literature employing blind source separation methods
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Recursive approach of EEG-segment-based principal component analysis substantially reduces cryogenic pump artifacts in simultaneous EEG–fMRI data
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System Identification through Nonstationary Response: Wavelet and Transformed Singular Value Decomposition—Based Approach
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References
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Independent component analysis: algorithms and applications
Aapo Hyvärinen,Erkki Oja +1 more
TL;DR: The basic theory and applications of ICA are presented, and the goal is to find a linear representation of non-Gaussian data so that the components are statistically independent, or as independent as possible.
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Fast and robust fixed-point algorithms for independent component analysis
TL;DR: Using maximum entropy approximations of differential entropy, a family of new contrast (objective) functions for ICA enable both the estimation of the whole decomposition by minimizing mutual information, and estimation of individual independent components as projection pursuit directions.
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Blind signal separation: statistical principles
TL;DR: The objectives of this paper are to review some of the approaches that have been developed to address blind signal separation and independent component analysis, to illustrate how they stem from basic principles, and to show how they relate to each other.
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High-order contrasts for independent component analysis
TL;DR: This article considers high-order measures of independence for the independent component analysis problem and discusses the class of Jacobi algorithms for their optimization and compares the proposed approaches with gradient-based techniques from the algorithmic point of view and also on a set of biomedical data.
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Independent component analysis by general nonlinear Hebbian-like learning rules
Aapo Hyvärinen,Erkki Oja +1 more
TL;DR: It is shown that in fact, ICA can be performed by very simple Hebbian or anti-Hebbian learning rules, which may have only weak relations to such information-theoretical quantities.