Bayesian Compressive Sensing Using Laplace Priors
Citations
623 citations
Cites background or methods from "Bayesian Compressive Sensing Using ..."
...As an example, a Laplace signal prior leads to a maximum a posteriori (MAP) optimal estimate that coincides with an optimal solution to the optimization[10]....
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...Similar approaches have been used in standard Bayesian CS methods [9], [10]....
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...According to [10], for both and are Laplace distributed and share the same PDF that is strongly peaked at the origin....
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318 citations
Cites background or methods from "Bayesian Compressive Sensing Using ..."
...In addition, BCS approaches [9] have been investigated for solving the perturbed CS problem [68]....
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...Due to their effectiveness, which often outperforms deterministic CS strategies in terms of reconstruction accuracy and robustness [8, 9, 47, 48, 51], as well as the availability of standard implementations of BCS and MT-BCS techniques [50], BCS with Laplace prior algorithms [51], and fast Bayesian matching pursuit [52] techniques, Bayesian approaches have been widely adopted in electromagnetics (see Section 4)....
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...For instance, “hierarchical-Laplace” priors on x have been included in [8, 9] by replacing (21) with PðxÞ 1⁄4 2 exp 2 kxk‘1 (25)...
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...Early developments included the application of CS strategies to imaging problems linearized through the Born approximation (BA) and comprising Laplace priors [9], as envisaged in [77–79]....
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...For example, the off-grid DoA detection has been formulated with Laplace priors in [9] with enhanced performances with respect to [18], but at the expense of a slower speed, particularly when a dense angular grid (i....
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294 citations
Cites background from "Bayesian Compressive Sensing Using ..."
...They include providing probabilistic prediction and automatic estimation of model parameters [22], [23]....
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232 citations
Cites background or methods from "Bayesian Compressive Sensing Using ..."
...With Bayesian linear regression, Hoffmann et al. [16] introduced BLDA to EEG classification for P300-based BCIs....
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...Currently, one of the most popularly adopted EEG patterns for BCI development is event-related potential (ERP), which is time- and phase-locked to stimulus events of interest [6]–[8]....
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202 citations
Cites methods from "Bayesian Compressive Sensing Using ..."
...Exploiting sparsity probabilistic model [18], many algorithms based on the LVA are proposed to solve the sparse decomposition problems [19, 11, 20, 21, 22, 14]....
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References
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"Bayesian Compressive Sensing Using ..." refers methods in this paper
...In the type-II maximum likelihood procedure, we represent by a degenerate distribution where the distribution is replaced by a delta function at its mode, where we assume that this posterior distribu- tion is sharply peaked around its mode [22]....
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9,950 citations
"Bayesian Compressive Sensing Using ..." refers methods in this paper
...Most of the proposed methods are examples of energy minimization methods, including linear programming algorithms [7], [8] and constructive (greedy) algorithms [9]–[11]....
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