Sequential adaptive compressed sampling via Huffman codes

Details Sequential adaptive compressed sampling via Huffman codes Sequential adaptive compressed sampling via Huffman codes

2008-10-27

arxiv.org/abs/0810.4916v2

Computer Science

Information Theory

4 figures, 13 pages

Scientific paper

There are two main approaches in compressed sensing: the geometric approach and the combinatorial approach. In this paper we introduce an information theoretic approach and use results from the theory of Huffman codes to construct a sequence of binary sampling vectors to determine a sparse signal. Unlike other approaches, our approach is adaptive in the sense that each sampling vector depends on the previous sample. The number of measurements we need for a k-sparse vector in n-dimensional space is no more than O(k log n) and the reconstruction is O(k).

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