magni.cs.reconstruction.it package

Subpackage providing implementations of Iterative Thresholding (IT).

Routine listings

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

Notes

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].

References

[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.