Results 21 to 30 of about 268,605 (307)
Sensors, 2017 This paper considers the complex-valued mixing matrix estimation and direction-of-arrival (DOA) estimation of synchronous orthogonal frequency hopping (FH) signals in the underdetermined blind source separation (UBSS).
Chaozhu Zhang, Yu Wang, Fulong Jing
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Entropy, 2021 In practical engineering applications, the vibration signals collected by sensors often contain outliers, resulting in the separation accuracy of source signals from the observed signals being seriously affected.
Jindong Wang +4 more
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Viability of perturbative renormalization factors in lattice QCD calculation of the K0-K¯0 mixing matrix [PDF]
, 1993 Validity of perturbative estimation of renormalization factors in weak matrix element calculations in lattice QCD is examined for the K0-K¯0 mixing matrix by comparing results for gauge invariant and noninvariant operators. A large disagreement found for
Fukugita M. +7 more
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Gain-Phase Errors Calibration for a Linear Array Based on Blind Signal Separation
Sensors, 2020 In this paper, a non-iterative blind calibration algorithm for gain-phase errors is proposed. A mixing matrix is first obtained from the received observation data through blind signal separation.
Zheng Dai, Weimin Su, Hong Gu
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Blind Source Separation Method for Bearing Vibration Signals
IEEE Access, 2018 In underdetermined blind source separation (UBSS) of vibration signals, the estimation of the mixing matrix is often affected by noise and by the type of the used clustering algorithm.
He Jun +4 more
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Probability density estimation with tunable kernels using orthogonal forward regression [PDF]
, 2009 A generalized or tunable-kernel model is proposed for probability density function estimation based on an orthogonal forward regression procedure. Each stage of the density estimation process determines a tunable kernel, namely, its center vector and ...
Chen, S., Harris, Chris J., Hong, Xia
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IEEE Access, 2019 Underdetermined blind source separation (UBSS) is a hot and challenging problem in signal processing. In the traditional UBSS algorithm, the number of source signals is often assumed to be known, which is very inconvenient in practice. In addition, it is
Yuan Xie, Kan Xie, Shengli Xie
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Blind separation of underdetermined mixtures with additive white and pink noises [PDF]
, 2014 This paper presents an approach for underdetermined blind source separation in the case of additive Gaussian white noise and pink noise. Likewise, the proposed approach is applicable in the case of separating I + 3 sources from I mixtures with additive
Alshabrawy, Ossama +3 more
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Bayesian source separation with mixture of Gaussians prior for sources and Gaussian prior for mixture coefficients [PDF]
, 2001 In this contribution, we present new algorithms to source separation for the case of noisy instantaneous linear mixture, within the Bayesian statistical framework.
Mohammad-Djafari, Ali, Snoussi, Hichem
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Estimating the mixing matrix by using less sparsity
Progress in Natural Science, 2009 Abstract In this paper, the nonlinear projection and column masking (NPCM) algorithm is proposed to estimate the mixing matrix for blind source separation. It preserves the samples which are close to the interested direction while suppressing the rest.
Zhou, Guoxu +3 more
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