Blind Source Separation and Sparse Bump Modelling of Time Frequency Representation of Eeg Signals: New Tools for Early Detection of Alzheimer’s Disease

2006 ◽  
Author(s):  
F. Vialatte ◽  
A. Cichocki ◽  
G. Dreyfus ◽  
T. Musha ◽  
T.M. Rutkowski ◽  
...  
Keyword(s):  
Early Detection ◽  
Blind Source Separation ◽  
Source Separation ◽  
Eeg Signals ◽  
Time Frequency ◽  
Frequency Representation

scholarly journals An Underdetermined Blind Source Separation Method with Application to Modal Identification

2019 ◽  
Vol 2019 ◽  
pp. 1-15 ◽  
Author(s):  
Gang Yu
Keyword(s):  
Blind Source Separation ◽  
Source Separation ◽  
Modal Identification ◽  
Modal Parameters ◽  
Underdetermined Blind Source Separation ◽  
Structural Dynamic ◽  
Time Frequency ◽  
Modal Response ◽  
Experimental Validations ◽  
Straight Lines

In structural dynamic analysis, the blind source separation (BSS) technique has been accepted as one of the most effective ways for modal identification, in which how to extract the modal parameters using very limited sensors is a highly challenging task in this field. In this paper, we first review the drawbacks of the conventional BSS methods and then propose a novel underdetermined BSS method for addressing the modal identification with limited sensors. The proposed method is established on the clustering features of time-frequency (TF) transform of modal response signals. This study finds that the TF energy belonging to different monotone modals can cluster into distinct straight lines. Meanwhile, we provide the detailed theorem to explain the clustering features. Moreover, the TF coefficients of each modal are employed to reconstruct all monotone signals, which can benefit to individually identify the modal parameters. In experimental validations, two experimental validations demonstrate the effectiveness of the proposed method.

Mathematical view of a blind source separation on a time frequency space

2007 ◽  
Vol 187 (1) ◽  
pp. 153-162 ◽  
Author(s):  
Keiko Fujita ◽  
Yoshitsugu Takei ◽  
Akira Morimoto ◽  
Ryuichi Ashino
Keyword(s):  
Blind Source Separation ◽  
Source Separation ◽  
Frequency Space ◽  
Time Frequency
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