Name
Abstract | ||
|---|---|---|
This paper introduces Golay-paired Hadamard matrices for fast compressed sensing of sparse signals in the time or spectral domain. These sampling operators feature low-memory requirement, hardware-friendly implementation and fast computation in reconstruction. We show that they require a nearly optimal number of measurements for faithful reconstruction of a sparse signal in the time or frequency domain. Simulation results demonstrate that the proposed sensing matrices offer a reconstruction performance similar to that of fully random matrices. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1109/ITW.2012.6404755 | ITW |
Keywords | Field | DocType |
time domain,fourier transform,compressed sensing,sparse signal,data compression,golay-paired hadamard matrix,sampling operator,hadamard matrix,hadamard matrices,spectral domain,golay sequence,dct,signal reconstruction,fast compressed sensing,sampling methods | Frequency domain,Computer science,Matrix (mathematics),Theoretical computer science,Binary Golay code,Data compression,Hadamard transform,Signal reconstruction,Compressed sensing,Random matrix | Conference |
ISBN | Citations | PageRank |
978-1-4673-0222-7 | 6 | 0.52 |
References | Authors | |
13 | 3 | |