Data Separation by Sparse Representations
نویسنده
چکیده
Recently, sparsity has become a key concept in various areas of applied mathematics, computer science, and electrical engineering. One application of this novel methodology is the separation of data, which is composed of two (or more) morphologically distinct constituents. The key idea is to carefully select representation systems each providing sparse approximations of one of the components. Then the sparsest coefficient vector representing the data within the composed – and therefore highly redundant – representation system is computed by l1 minimization or thresholding. This automatically enforces separation. This paper shall serve as an introduction to and a survey about this exciting area of research as well as a reference for the state-of-the-art of this research field.
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عنوان ژورنال:
- CoRR
دوره abs/1102.4527 شماره
صفحات -
تاریخ انتشار 2011