153 citations to https://www.mathnet.ru/rus/tit3
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Natarajan Pradeepa, Chenthur Pandian Ram Kumar, Sakkanan Chenthur Pandian, “Compressive Sensing-Based Diagnosis of Diabetic Retinopathy from Fundus Image – A Sparse Approach”, IETE Journal of Research, 68:2 (2022), 833
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Sami Doubla Isaac, Zeric Tabekoueng Njitacke, Nestor Tsafack, Christian Tchito Tchapga, Jacques Kengne, “Novel compressive sensing image encryption using the dynamics of an adjustable gradient Hopfield neural network”, Eur. Phys. J. Spec. Top., 231:10 (2022), 1995
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Chunfang Shao, Jincai Chang, Peixin Ye, Wenhui Zhang, Shuo Xing, “Almost Optimality of the Orthogonal Super Greedy Algorithm for μ-Coherent Dictionaries”, Axioms, 11:5 (2022), 186
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Wael Saideni, David Helbert, Fabien Courreges, Jean-Pierre Cances, “An Overview on Deep Learning Techniques for Video Compressive Sensing”, Applied Sciences, 12:5 (2022), 2734
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Lin Xu, Xiangyong Cao, Jing Yao, Zheng Yan, “Orthogonal Super Greedy Learning for Sparse Feedforward Neural Networks”, IEEE Trans. Netw. Sci. Eng., 9:1 (2022), 161
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Seungwoo Hong, Dongyun Kam, Sangbu Yun, Jeongwon Choe, Namyoon Lee, Youngjoo Lee, “Low-Complexity and Low-Latency SVC Decoding Architecture Using Modified MAP-SP Algorithm”, IEEE Trans. Circuits Syst. I, 69:4 (2022), 1774
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Shri Ramtej K., Ramasamy Mariappan, Advances in Computer and Electrical Engineering, 5G Internet of Things and Changing Standards for Computing and Electronic Systems, 2022, 134
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Xiwen Zhang, Liejun Xie, Jinping Wang, “Some results on OMP algorithm for MMV problem”, Math Methods in App Sciences, 45:9 (2022), 5402
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Ryo Hayakawa, “Asymptotic Performance Prediction for ADMM-Based Compressed Sensing”, IEEE Trans. Signal Process., 70 (2022), 5194
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Saumya Patel, Ankita Vaish, Algorithms for Intelligent Systems, Machine Intelligence and Smart Systems, 2022, 199