On the Performance of Turbo Signal Recovery with Partial DFT Sensing Matrices
Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review
Author(s)
Related Research Unit(s)
Detail(s)
Original language | English |
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Article number | 7065244 |
Pages (from-to) | 1580-1584 |
Journal / Publication | IEEE Signal Processing Letters |
Volume | 22 |
Issue number | 10 |
Online published | 23 Mar 2015 |
Publication status | Published - Oct 2015 |
Link(s)
Abstract
This letter is on the performance of the turbo signal recovery (TSR) algorithm for partial discrete Fourier transform (DFT) matrices based compressed sensing. Based on state evolution analysis, we prove that TSR with a partial DFT sensing matrix outperforms the well-known approximate message passing (AMP) algorithm with an independent identically distributed (IID) sensing matrix.
Research Area(s)
- AMP, partial DFT, signal recovery, state evolution, turbo compressed sensing
Citation Format(s)
On the Performance of Turbo Signal Recovery with Partial DFT Sensing Matrices. / Ma, Junjie; Yuan, Xiaojun; Ping, Li.
In: IEEE Signal Processing Letters, Vol. 22, No. 10, 7065244, 10.2015, p. 1580-1584.
In: IEEE Signal Processing Letters, Vol. 22, No. 10, 7065244, 10.2015, p. 1580-1584.
Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review