Event Details
Unconstrained Approximate Lp-Norm Based Algorithm for the Reconstruction of Sparse Signals
Presenter: Jeevan K. Pant, PhD student
Supervisor: Drs. Andreas Antoniou and Wu-Sheng Lu
Date: Tue, April 3, 2012
Time: 13:00:00 - 00:00:00
Place: EOW 430
ABSTRACT
Abstract:
A new algorithm for signal reconstruction in a compressive sensing framework is presented. The algorithm is based on minimizing an unconstrained approximate Lp norm with p < 1 in the null space of the measurement matrix. The unconstrained optimization involved is performed by using a quasi-Newton algorithm in which a new line search based on Banach's fixed-point theorem is used. Simulation results are presented, which demonstrate that the proposed algorithm yields improved reconstruction performance and requires a reduced amount of computation relative to several known algorithms.