NDLI: Efficient blind source extraction of noisy mixture utilising a class of parallel linear predictor filters

Content Provider	IET Digital Library
Author	Taha, Luay Yassin Raheem, Esam Abdel
Abstract	This study presents a novel blind source extraction of a noisy mixture using a class of parallel linear predictor filters. Analysis of a noisy mixture equation is carried out to address new autoregressive source signal model based on the covariance matrix of the whitened data. A method of interchanging the rules of filter inputs is proposed such that this matrix becomes the filter input while the estimated source signals are considered as the parallel filter coefficients. As the matrix has unity norm and unity eigenvalues, the filter becomes independent on the mixture signal norm and eigenvalues variations, thus solving drastically the ambiguity due to the dependency of the filter on the mixture power levels if the mixture is considered as the filter input. Furthermore, the unity eigenvalues of the matrix result in a very fast convergence in two iterations. Simulation results show that the model is capable of extracting the unknown source signals and removing noise when the input signal-to-noise ratio is varied from −20 to 80 dB.
Starting Page	1009
Ending Page	1016
Page Count	8
ISSN	17519675
Volume Number	12
e-ISSN	17519683
Issue Number	Issue 8, Oct (2018)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-spr/12/8
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-spr.2017.0512
Journal	IET Signal Processing
Publisher Date	2018-05-04
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Autoregressive Processes Autoregressive Source Signal Model Blind Source Extraction Blind Source Separation Covariance Matrices Covariance Matrix Eigen Values And Eigen Function Eigenvalues Variations Feature Extraction Filtering Method in Signal Processing Filtering Theory Input Signal-to-noise Ratio Interpolation And Function Approximation Iterative Method Linear Algebra Mixture Power Levels Mixture Signal Norm Noisy Mixture Equation Analysis Numerical Analysis Parallel Filter Coefficient Parallel Linear Predictor Filter Signal Processing Theory Source Signal Estimation Statistics Unity EigenValue Unity Norm Matrix Whitened Data
Content Type	Text
Resource Type	Article
Subject	Signal Processing Electrical and Electronic Engineering

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