lP minimization for sparse vector reconstruction

  • Authors:

  • N. Mourad;James P. Reilly

  • Affiliations:

  • Department of Electrical&Computer Eng., McMaster University, 1280 Main St. W., Hamilton, Ontario, Canada L8S 4K1;Department of Electrical&Computer Eng., McMaster University, 1280 Main St. W., Hamilton, Ontario, Canada L8S 4K1

  • Venue:
  • ICASSP '09 Proceedings of the 2009 IEEE International Conference on Acoustics, Speech and Signal Processing
  • Year:
  • 2009

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Abstract

In this paper we present a new technique for minimizing a class of nonconvex functions for solving the problem of under-determined systems of linear equations. The proposed technique is based on locally replacing the nonconvex objective function by a convex objective function. The main property of the utilized convex function is that it is minimized at a point that reduces the original concave function. The resulting algorithm is iterative and outperforms some previous algorithms that have been applied to the same problem.