Sequential adaptive compressed sampling via Huffman codes

In this paper we introduce an information theoretic approach and use techniques from the theory of Huffman codes to construct a sequence of binary sampling vectors to determine a sparse signal. Unlike other approaches, ours is adaptive in the sense that each sampling vector depends on the previous sample results. The expected total cost (number of measurements and reconstruction combined) we need for an s-sparse vector in Rn is no more than s log n + 2s.

• Type: Journal
• Year: 2008
• Where: CORR
• Authors: Akram Aldroubi, Haichao Wang, Kourosh Zarringhalam
• Keywords: Binary Sampling Vectors, CORR 2008, Education, Information Theoretic Approach, Sparse Signal