Subpackage providing implementations of Iterative Thresholding (IT).

Routine listings

Configger providing configuration options for this subpackage.
run(y, A)
Run the IT reconstruction algorithm.


Implementations of Iterative Hard Thresholding (IHT) [1], [2] as well as implementations of Iterative Soft Thresholding (IST) [3], [4] are available. It is also possible to configure the subpackage to use a model based approach as described in [5].


[1]T. Blumensath and M.E. Davies, “Iterative Thresholding for Sparse Approximations”, Journal of Fourier Analysis and Applications, vol. 14, pp. 629-654, Sep. 2008.
[2]T. Blumensath and M.E. Davies, “Normalized Iterative Hard Thresholding: Guaranteed Stability and Performance”, IEEE Journal Selected Topics in Signal Processing, vol. 4, no. 2, pp. 298-309, Apr. 2010.
[3]I. Daubechies, M. Defrise, and C. D. Mol, “An Iterative Thresholding Algorithm for Linear Inverse Problems with a Sparsity Constraint”, Communications on Pure and Applied Mathematics, vol. 57, no. 11, pp. 1413-1457, Nov. 2004.
[4]A. Maleki and D.L. Donoho, “Optimally Tuned Iterative Reconstruction Algorithms for Compressed Sensing”, IEEE Journal Selected Topics in Signal Processing, vol. 3, no. 2, pp. 330-341, Apr. 2010.
[5]R.G. Baraniuk, V. Cevher, M.F. Duarte, and C. Hedge, “Model-Based Compressive Sensing”, IEEE Transactions on Information Theory, vol. 56, no. 4, pp. 1982-2001, Apr. 2010.