Sparse sampling: theory, methods and an application in neuroscience
نویسندگان
چکیده
منابع مشابه
Sampling Functions and Sparse Reconstruction Methods
SUMMARY In this paper we investigate the effects of different sampling operators on the performance of sparse reconstruction methods. The common paradigm in seismic data processing is to favor regular sampling. We will show, however, that regular sampling often hampers our data recovery efforts. Random sampling, on the other hand, can lead to algorithms where the reconstruction is almost perfec...
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The study of sparsity has recently garnered significant attention in the signal processing and statistics communities. Generally speaking, sparsity describes the phenomenon where a large data set may be succinctly represented or approximated using only a small number of summary values or coefficients. The implications are clear—the presence of sparsity suggests the potential for efficient metho...
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ژورنال
عنوان ژورنال: Biological Cybernetics
سال: 2014
ISSN: 0340-1200,1432-0770
DOI: 10.1007/s00422-014-0639-x