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Underdetermined Mixing Matrix Estimation Algorithm Based on Single Source Points
Circuits, Systems, and Signal Processing, 2017zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Qiang Guo, Guoqing Ruan, Pulong Nan
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Novel mixing matrix estimation approach in underdetermined blind source separation
Neurocomputing, 2016This paper proposes the use of density-based spatial clustering of application with noise (DBSCAN) and the Hough transform to estimate the mixing matrix in underdetermined blind source separation. First, phase-angle-based single source time-frequency point detection is employed to improve signal sparsity.
Jiedi Sun +3 more
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A fast mixing matrix estimation method in the wavelet domain
Signal Processing, 2013 In the field of blind image separation (BIS) based on the sparse component analysis, separation efficiency and accuracy are directly affected by the number of clustering samples. To address this problem, a new algorithm for the detection of points in the Haar wavelet domain was proposed in which only single source contributions occur.
Jindong Xu +3 more
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A Complex Mixing Matrix Estimation Algorithm Based on Single Source Points
Circuits, Systems, and Signal Processing, 2015zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Li, Yibing, Nie, Wei, Ye, Fang
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Mixing Matrix Estimation From Sparse Mixtures With Unknown Number of Sources
IEEE Transactions on Neural Networks, 2010 In blind source separation, many methods have been proposed to estimate the mixing matrix by exploiting sparsity. However, they often need to know the source number a priori, which is very inconvenient in practice. In this paper, a new method, namely nonlinear projection and column masking (NPCM), is proposed to estimate the mixing matrix.
Guoxu Zhou +3 more
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Mixing matrix estimation using discriminative clustering for blind source separation
Digital Signal Processing, 2013Mixing matrix estimation in instantaneous blind source separation (BSS) can be performed by exploiting the sparsity and disjoint orthogonality of source signals. As a result, approaches for estimating the unknown mixing process typically employ clustering algorithms on the mixtures in a parametric domain, where the signals can be sparsely represented ...
Jayaraman J. Thiagarajan +2 more
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Underdetermined Mixing Matrix Estimation Based on Single Source Detection
2018 China International SAR Symposium (CISS), 2018 In this paper, a new underdetermined mixing matrix estimation method for Blind Source Separation (BSS) from linear time delay mixture is developed based on Single-Source Point (SSP) detection. Firstly, prior knowledge of linear time delay mixtures are extracted with the help of receive antennas, and then the rule is derived to determine the SSPs. After
Liangjun Zhang +5 more
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Underdetermined mixing matrix estimation based on joint density-based clustering algorithms
Multimedia Tools and Applications, 2020 In underdetermined blind source separation (UBSS), the estimation of the mixing matrix is crucial because it directly affects the performance of UBSS. To improve the estimation accuracy, this paper proposes a joint clustering analysis method based on density based spatial clustering of applications with noise (DBSCAN) and clustering by fast search and ...
Xuansen He, Fan He, Li Xu
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Underdetermined mixing matrix estimation by exploiting sparsity of sources
Measurement, 2019 Abstract To estimate the mixing matrix in underdetermined mixing systems, we propose a novel method by exploiting the sparsity of sources. We utilize the pairwise relationships among all of the mixture representations to detect the single source points in the time-frequency (TF) domain, i.e., the positions where only one source contributed dominantly.
Liangli Zhen +4 more
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Blind Estimation of Underdetermined Mixing Matrix Based on Density Measurement
Wireless Personal Communications, 2018Under the circumstances that source signals are sufficiently sparse, an algorithm based on density measurement for blind estimation of the underdetermined mixing matrix is proposed in this paper. The proposed algorithm can estimate the number of source signals and the mixing matrix of the transmission channel simultaneously without any prior ...
Weihong Fu +4 more
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