Bayesian Compressed Sensing using Alpha-Stable Distributions (2009)
Abstract / truncated to 115 words
During the last decades, information is being gathered and processed at an explosive rate. This fact gives rise to a very important issue, that is, how to effectively and precisely describe the information content of a given source signal or an ensemble of source signals, such that it can be stored, processed or transmitted by taking into consideration the limitations and capabilities of the several digital devices. One of the fundamental principles of signal processing for decades is the Nyquist-Shannon sampling theorem, which states that the minimum number of samples needed to reconstruct a signal without error is dictated by its bandwidth. However, there are many cases in our everyday life in which sampling at ... toggle 4 keywordsbayesian compressed sensing – alpha-stable models – heavy-tailed distributions – distributed compressed sensing
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