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Newton-Type Optimal Thresholding Algorithms for Sparse Optimization Problems
In this paper, we propose the so-called Newton-type optimal $k$-thresholding (NTOT) algorithm which is motivated by the appreciable performance of both Newton-type methods and the optimal $k$-thresholding technique for signal recovery.
Improved RIP-Based Bounds for Guaranteed Performance of two Compressed Sensing Algorithms
The purpose of this paper is to affirmatively answer this question and rigorously show that the RIP-based bounds for guaranteed performance of IHT can be significantly improved to $ \delta_{3k} < (\sqrt{5}-1)/2 \approx 0. 618, $ and the bound for CoSaMP can be improved and pushed to $ \delta_{4k}< 0. 5102.
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