$l_{q}$ Sparsity Penalized Linear Regression With Cyclic Descent

@article{Marjanovic2014l_qS,
  title={\$l_\{q\}\$  Sparsity Penalized Linear Regression With Cyclic Descent},
  author={Goran Marjanovic and Victor Solo},
  journal={IEEE Transactions on Signal Processing},
  year={2014},
  volume={62},
  pages={1464-1475}
}
Recently, there has been a lot of focus on penalized least squares problems for noisy sparse signal estimation. The penalty induces sparsity and a very common choice has been the convex l1 norm. However, to improve sparsity and reduce the biases associated with the l1 norm, one must move to non-convex penalties such as the lq norm . In this paper we present a novel cyclic descent algorithm for optimizing the resulting lq penalized least squares problem. Optimality conditions for this problem… CONTINUE READING

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