NDLI: Dual estimation approach to blind source separation

Content Provider	IET Digital Library
Author	Langkam, Sabita Deb, Alok Kanti
Abstract	A dual estimation approach has been proposed towards solving the blind source separation (BSS) problem. The states and the parameters of the dynamical system are estimated simultaneously when only noisy observations are available. The framework assumed for dual estimation is that of dual Kalman filtering. Two separate Kalman filters run simultaneously, the state filter which runs for state estimation and uses the current estimate of the parameters and the parameter filter which runs for parameter estimation and uses the current state estimates. The study of the information theoretical analysis of Kalman filter shows that the filter in its process maximises the mutual information between a state and the estimate indicating that the filter may be a potential solution for BSS problems. The proposed state-space-based dual estimation approach, dual Kalman BSS, has been studied for linear instantaneous BSS and the simulation results validate the proposed approach. The performance comparison carried out against the FastICA, joint-approximate diagonalisation of Eigenmatrices, k-temporal decorrelation separation and BSS algorithm by Zhang, Woo and Dlay for post-non-linear convolutive modelling in terms of signal-to-interference ratio and signal-to-distortion ratio shows that for a good intuitive initialization the proposed approach does better separation.
Starting Page	527
Ending Page	536
Page Count	10
ISSN	17519675
Volume Number	11
e-ISSN	17519683
Issue Number	Issue 5, Jul (2017)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-spr/11/5
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-spr.2016.0357
Journal	IET Signal Processing
Publisher Date	2017-01-23
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Approximation Theory Blind Source Separation Dual Estimation Approach Dual Kalman Filtering Eigenmatrices Joint-approximate Diagonalisation FastICA Filtering Method in Signal Processing Interpolation And Function Approximation K-temporal Decorrelation Separation Kalman Filter Linear Algebra Matrix Algebra Modelling And Identification Numerical Analysis Post-non-linear Convolutive Modelling Signal Processing Theory Signal-to-interference Ratio Simulation State Estimation
Content Type	Text
Resource Type	Article
Subject	Signal Processing Electrical and Electronic Engineering

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