1-bit Hamming compressed sensing

Publication Type:
Conference Proceeding
IEEE International Symposium on Information Theory - Proceedings, 2012, pp. 1862 - 1866
Issue Date:
Full metadata record
Files in This Item:
Filename Description SizeFormat
2012004232OK.pdf508.09 kBAdobe PDF
Compressed sensing (CS) and 1-bit CS cannot directly recover quantized signals preferred in digital systems and require time consuming recovery. In this paper, we introduce 1-bit Hamming compressed sensing (HCS) that directly recovers a k-bit quantized signal of dimension n from its 1-bit measurements via invoking n times of Kullback-Leibler divergence based nearest neighbor search. Compared to CS and 1-bit CS, 1-bit HCS allows the signal to be dense, takes considerably less (linear and non-iterative) recovery time and requires substantially less measurements. Moreover, 1-bit HCS can accelerate 1bit CS recover. We study a quantized recovery error bound of 1-bit HCS for general signals. Extensive numerical simulations verify the appealing accuracy, robustness, efficiency and consistency of 1-bit HCS.
Please use this identifier to cite or link to this item: