On a method for testing ICA based Blind Source Separation algorithm performance applicable in audiobased On-Load Tap Changer diagnostics

2018 ◽  
Author(s):  
A. Secic ◽  
N. Hlupic ◽  
I. Kuzle
Keyword(s):  
Blind Source Separation ◽  
Source Separation ◽  
Separation Algorithm ◽  
Algorithm Performance ◽  
Tap Changer ◽  
Load Tap Changer

Extraction of fetal ECG a semi-blind source separation algorithm combined with parametrized kalman filter

2021 ◽  
Author(s):  
J. Sakubar Sadiq ◽  
G. Arunmani ◽  
P. Ravivarma ◽  
N. Karthika Devi ◽  
A. Hemalatha ◽  
...  
Keyword(s):  
Kalman Filter ◽  
Blind Source Separation ◽  
Source Separation ◽  
Separation Algorithm ◽  
Fetal Ecg

Blind Complex Source Separation Based on Cyclostationary Statistics

2014 ◽  
Vol 519-520 ◽  
pp. 1051-1056
Author(s):  
Jie Guo ◽  
An Quan Wei ◽  
Lei Tang
Keyword(s):  
Blind Source Separation ◽  
Source Separation ◽  
Separation Performance ◽  
Separation Algorithm ◽  
Complex Signals ◽  
Cyclic Frequency ◽  
Complex Source ◽  
Simulation Results ◽  
Better Than ◽  
Separation Model

This paper analyzed a blind source separation algorithm based on cyclic frequency of complex signals. Under the blind source separation model, we firstly gave several useful assumptions. Then we discussed the derivation of the BSS algorithm, including the complex signals and the normalization situation. Later, we analyzed the complex WCW-CS algorithm, which was compared with NGA, NEASI and NGA-CS algorithms. Simulation results show that the complex WCW-CS algorithm has the best convergence and separation performance. It can also effectively separate mixed image signals, whose performance was better than NGA algorithm.

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