Results 21 to 30 of about 981,446 (269)
Orthogonal Matching Pursuit for Text Classification [PDF]
Proceedings of the 2018 EMNLP Workshop W-NUT: The 4th Workshop on Noisy User-generated Text, 2018 In text classification, the problem of overfitting arises due to the high dimensionality, making regularization essential. Although classic regularizers provide sparsity, they fail to return highly accurate models. On the contrary, state-of-the-art group-lasso regularizers provide better results at the expense of low sparsity. In this paper, we apply a
Konstantinos Skianis +2 more
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Electrical Faults Signals Restoring Based on Compressed Sensing Techniques
Energies, 2020 This research focuses on restoring signals caused by power failures in transmission lines using the basis pursuit, matching pursuit, and orthogonal matching pursuit sensing techniques.
Milton Ruiz, Iván Montalvo
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Perturbation Analysis of Orthogonal Matching Pursuit [PDF]
IEEE Transactions on Signal Processing, 2013 29 ...
Jie Ding, Laming Chen, Yuantao Gu
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Journal of Low Frequency Noise, Vibration and Active Control, 2021 This paper proposes a direction of arrival estimation based on sparse signal reconstruction in the presence of alpha noise by the off-grid orthogonal matching pursuit algorithm.
LongKai Liang +3 more
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Temperature Field Reconstruction Method for Acoustic Tomography Based on Multi-Dictionary Learning
Sensors, 2022 A reconstruction algorithm is proposed, based on multi-dictionary learning (MDL), to improve the reconstruction quality of acoustic tomography for complex temperature fields.
Yuankun Wei, Hua Yan, Yinggang Zhou
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Efficient Distributed Multi-Task Schemes for mmWave MIMO Channel Estimation
IEEE Access, 2022 In this study, the problem of sparse channel estimation is investigated with the employment of a fully distributed approach. We exploit the spatially joint sparsity structure of the involved channels to formulate the channel estimation problem in the ...
Maria Trigka +2 more
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Rapid Estimation of Orthogonal Matching Pursuit Representation [PDF]
IGARSS 2020 - 2020 IEEE International Geoscience and Remote Sensing Symposium, 2020 Orthogonal Matching Pursuit (OMP) has proven itself to be a significant algorithm in image and signal processing domain in the last decade to estimate sparse representations in dictionary learning. Over the years, efforts to speed up the OMP algorithm for the same accuracy has been through variants like generalized OMP (g-OMP) and fast OMP (f-OMP). All
Ayan Chatterjee, Peter W. T. Yuen
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GRADIENT POLYTOPE FACES PURSUIT FOR LARGE SCALE SPARSE RECOVERY PROBLEMS [PDF]
, 2010 IEEE International Conference on Acoustics Speech and Signal Processing (ICASSP), Dallas, TX, 14-19 March ...
Gretsistas, A +2 more
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A Low-complexity Sparse Channel Estimation Algorithm [PDF]
Jisuanji gongcheng, 2016 Traditional Compressed Sensing(CS)based channel estimation methods are difficult to implement due to their high computational complexity.To solve this problem,Generalized Orthogonal Matching Pursuit(GOMP)algorithm is used for channel estimation,which ...
FAN Xinyue,SU Yantao,ZHOU Fei
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, 2008 Sparse signal approximations have become a fundamental tool in signal processing with wide ranging applications from source separation to signal acquisition.
Blumensath, T. +2 more
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