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Natural Thresholding Algorithms for Signal Recovery With Sparsity [PDF]
IEEE Open Journal of Signal Processing, 2022 The algorithms based on the technique of optimal $k$-thresholding (OT) were recently proposed for signal recovery, and they are very different from the traditional family of hard thresholding methods.
Yun-Bin Zhao, Zhi-Quan Luo
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Signal Recovery by Stochastic Optimization [PDF]
Automation and Remote Control, 2019 We discuss an approach to signal recovery in Generalized Linear Models (GLM) in which the signal estimation problem is reduced to the problem of solving a stochastic monotone Variational Inequality (VI).
A. Juditsky, A. Nemirovski
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Recovery of Sparsely Corrupted Signals [PDF]
IEEE Transactions on Information Theory, 2012 We investigate the recovery of signals exhibiting a sparse representation in a general (i.e., possibly redundant or incomplete) dictionary that are corrupted by additive noise admitting a sparse representation in another general dictionary. This setup covers a wide range of applications, such as image inpainting, super-resolution, signal separation ...
Christoph Studer +2 more
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Sparse signal recovery from modulo observations
EURASIP Journal on Advances in Signal Processing, 2021 We consider the problem of reconstructing a signal from under-determined modulo observations (or measurements). This observation model is inspired by a relatively new imaging mechanism called modulo imaging, which can be used to extend the dynamic range ...
Viraj Shah, Chinmay Hegde
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Joint Channel Estimation and Signal Recovery for RIS-Empowered Multiuser Communications [PDF]
IEEE Transactions on Communications, 2021 Reconfigurable intelligent surfaces (RISs) have been recently considered as a promising candidate for energy-efficient solutions in future wireless networks.
Li Wei +7 more
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Heavy-Ball-Based Hard Thresholding Algorithms for Sparse Signal Recovery [PDF]
Journal of Computational and Applied Mathematics, 2022 The hard thresholding technique plays a vital role in the development of algorithms for sparse signal recovery. By merging this technique and heavy-ball acceleration method which is a multi-step extension of the traditional gradient descent method, we ...
Zhongxing Sun +3 more
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Proportionate Adaptive Graph Signal Recovery [PDF]
IEEE Transactions on Signal and Information Processing over Networks, 2022 This paper generalizes the proportionate-type adaptive algorithm to the graph signal processing and proposes two proportionate-type adaptive graph signal recovery algorithms. The gain matrix of the proportionate algorithm leads to faster convergence than
Razieh Torkamani +2 more
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Robust Time-Varying Graph Signal Recovery for Dynamic Physical Sensor Network Data [PDF]
IEEE Transactions on Signal and Information Processing over Networks, 2022 We propose a time-varying graph signal recovery method for estimating the true time-varying graph signal from corrupted observations by leveraging dynamic graphs.
Eisuke Yamagata +2 more
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Image-Label Recovery on Fashion Data Using Image Similarity from Triple Siamese Network
Technologies, 2021 Weakly labeled data are inevitable in various research areas in artificial intelligence (AI) where one has a modicum of knowledge about the complete dataset. One of the reasons for weakly labeled data in AI is insufficient accurately labeled data. Strict
Debapriya Banerjee +2 more
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The lock-in amplifier: what is it for? how to build one?
Revista Brasileira de Ensino de Física, 2022 A short description of the lock-in technique gives an idea of the working principle of these useful devices, that are spreadly used in weak signals detection, but rarely treated in introductory courses.
Giacomo Torzo, Giorgio Delfitto
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