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 -