TY - GEN
T1 - Variable projection and unfolding in compressed sensing
AU - Goodman, Joel
AU - Miller, Benjamin A.
AU - Raz, Gil
AU - Bolstad, Andrew
PY - 2007
Y1 - 2007
N2 - The performance of linear programming techniques that are applied in the signal identification and reconstruction process in compressed sensing (CS) is governed by both the number of measurements taken and the number of nonzero coefficients in the discrete basis used to represent the signal. To enhance the capabilities of CS, we have developed a technique called Variable Projection and Unfolding (VPU). VPU extends the identification and reconstruction capability of linear programming techniques to signals with a much greater number of nonzero coefficients in the basis in which the signals are compressible with significantly better reconstruction error.
AB - The performance of linear programming techniques that are applied in the signal identification and reconstruction process in compressed sensing (CS) is governed by both the number of measurements taken and the number of nonzero coefficients in the discrete basis used to represent the signal. To enhance the capabilities of CS, we have developed a technique called Variable Projection and Unfolding (VPU). VPU extends the identification and reconstruction capability of linear programming techniques to signals with a much greater number of nonzero coefficients in the basis in which the signals are compressible with significantly better reconstruction error.
UR - http://www.scopus.com/inward/record.url?scp=47849106012&partnerID=8YFLogxK
U2 - 10.1109/SSP.2007.4301280
DO - 10.1109/SSP.2007.4301280
M3 - Conference contribution
AN - SCOPUS:47849106012
SN - 142441198X
SN - 9781424411986
T3 - IEEE Workshop on Statistical Signal Processing Proceedings
SP - 358
EP - 362
BT - 2007 IEEE/SP 14th Workshop on Statistical Signal Processing, SSP 2007, Proceedings
T2 - 2007 IEEE/SP 14th WorkShoP on Statistical Signal Processing, SSP 2007
Y2 - 26 August 2007 through 29 August 2007
ER -