报告人：温金明 教授（暨南大学）

时间：2024年11月24日 17:00-

地点: 理科楼LA103

摘要：Recovering a non-negative sparse signal from an underdetermined linear system remains a challenging problem in signal processing. Despite the development of various approaches, such as non-negative least squares, as well as variants of greedy algorithms and iterative thresholding methods, their recovery performance and efficiency often fall short of practical expectations. Aiming to address this limitation, this paper first devises a momentum-boosted adaptive thresholding (MBAT) algorithm for non-negative sparse signal recovery. Then, we establish two sufficient conditions of stable recovery for the proposed algorithm by using the restricted isometry property and mutual coherence. Extensive tests based on synthetic and real-world data demonstrate the superiority of our approach over the state-of-the-art non-negative orthogonal greedy algorithms and iterative thresholding methods, in terms of the probability of successful recovery, phase transition, and computational attractiveness.

邀请人：吴风艳

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