Optimal k-thresholding for Sparse Signal Recovery

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• Yun-Bin Zhao (University of Birmingham)
• Wednesday 20 March 2019, 12:00-13:00
• Room R17/18, Watson building.

If you have a question about this talk, please contact Sergey Sergeev.

The existing hard thresholding methods may cause a dramatic increase and numerical oscillation of the residual. This inherit drawback renders the algorithms unstable and generally inefficient for solving practical compressed sensing problems. How to develop an efficient thresholding technique becomes a fundamental question in this area. In this presentation, the notion of optimal k-thresholding will be introduced and a new thresholding technique going beyond the existing frame will be discussed. This leads to a natural design principle for efficient thresholding algorithms. It turns out that the theoretical performance for the proposed optimal thresholding algorithms is guaranteed under an improved RIP bound. The numerical experiments demonstrate that the traditional hard-thresholding algorithms have been significantly transcended by our proposed algorithms which also outperform the classic l1-minimization method in sparse signal recovery.

This talk is part of the Optimisation and Numerical Analysis Seminars series.

This talk is included in these lists:

• Optimisation and Numerical Analysis Seminars
• Room R17/18, Watson building
• School of Mathematics events

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