dc.contributor.authorLiu, Benxu
dc.contributor.authorReju, V.
dc.contributor.authorKhong, Andy Wai Hoong
dc.identifier.citationLiu, B., Reju, V. G., & Khong, A. W. H. (2014). A linear source recovery method for underdetermined mixtures of uncorrelated AR-model signals without sparseness. IEEE transactions on signal processing, 62(19), 4947-4958.
dc.description.abstractConventional sparseness-based approaches for instantaneous underdetermined blind source separation (UBSS) do not take into account the temporal structure of the source signals. In this work, we exploit the source temporal structure and propose a linear source recovery solution for the UBSS problem which does not require the source signals to be sparse. Assuming the source signals are uncorrelated and can be modeled by an autoregressive (AR) model, the proposed algorithm is able to estimate the source AR coefficients from the mixtures given the mixing matrix. We prove that the UBSS problem can be converted into a determined problem by combining the source AR model together with the original mixing equation to form a state-space model. The Kalman filter is then applied to obtain a linear source estimate in the minimum mean-squared error sense. Simulation results using both synthetic AR signals and speech utterances show that the proposed algorithm achieves better separation performance compared with conventional sparseness-based UBSS algorithms.en_US
dc.relation.ispartofseriesIEEE transactions on signal processingen_US
dc.rights© 2013 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. The published version is available at: [http://dx.doi.org/10.1109/TSP.2014.2329646].en_US
dc.subjectElectrical and Electronic Engineering
dc.titleA linear source recovery method for underdetermined mixtures of uncorrelated AR-model signals without sparsenessen_US
dc.typeJournal Article
dc.contributor.schoolSchool of Electrical and Electronic Engineeringen_US
dc.description.versionAccepted versionen_US

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