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We investigate a hybrid method which improves the quality of state inference and parameter estimation in blind deconvolution of a sparse source modeled by a Bernoulli-Gaussian process. In this problem, when both the signal and the filter are jointly estimated, the true posterior is typically highly multimodal. Therefore, when not properly initialized, standard stochastic inference methods, (MCEM,...
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