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- W2048288071 abstract "This paper presents an online version of the widely used sparse Bayesian learning (SBL) algorithm. Exploiting the variational Bayes framework, an efficient online SBL algorithm is constructed, that acts as a fully automatic learning method for the adaptive estimation of sparse time-varying signals. The new method is based on second order statistics and comprises a simple, automated sparsity-imposing mechanism, different from that of other known schemes. The effectiveness of the proposed online Bayesian algorithm is illustrated using experimental results conducted on synthetic data. These results show that the proposed scheme achieves faster initial convergence and superior estimation performance compared to other related state-of-the-art schemes." @default.
- W2048288071 created "2016-06-24" @default.
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- W2048288071 date "2014-05-01" @default.
- W2048288071 modified "2023-09-23" @default.
- W2048288071 title "Adaptive variational sparse Bayesian estimation" @default.
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- W2048288071 doi "https://doi.org/10.1109/icassp.2014.6855094" @default.
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