Wavelet Reconstruction of Nonuniformly Sampled Signals
This document was originally published by IEEE in IEEE Signal Processing Letters. Copyright restrictions may apply. DOI: 10.1109/LSP.2008.2008939
For the reconstruction of a nonuniformly sampled signal based on its noisy observations, we propose a level dependent l1 penalized wavelet reconstruction method. The LARS/Lasso algorithm is applied to solve the Lasso problem. The data adaptive choice of the regularization parameters is based on the AIC and the degrees of freedom is estimated by the number of nonzero elements in the Lasso solution. Simulation results conducted on some commonly used 1_D test signals illustrate that the proposed method possesses good empirical properties.
Leming Qu, Partha S. Routh, and Phil D. Anno. "Wavelet Reconstruction of Nonuniformly Sampled Signals" IEEE Signal Processing Letters 16.2 (2009): 73-76.
Available at: http://works.bepress.com/leming_qu/4