Results 21 to 30 of about 20,110 (263)
Seismic random noise attenuation using modified wavelet thresholding
Annals of Geophysics, 2017 In seismic exploration, random noise deteriorates the quality of acquired data. This study analyzed existing denoising methods used in seismic exploration from the perspective of random noise. Wavelet thresholding offers a new approach to reducing random
Qi-sheng Zhang +5 more
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Soft Threshold Constraints for Pattern Mining [PDF]
, 2012 Constraint-based pattern discovery is at the core of numerous data mining tasks. Patterns are extracted with respect to a given set of constraints (frequency, closedness, size, etc). In practice, many constraints require threshold values whose choice is often arbitrary.
Ugarte Rojas, Willy +3 more
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Compressed Sensing Techniques Applied to Medical Images Obtained with Magnetic Resonance
Mathematics, 2023 The fast and reliable processing of medical images is of paramount importance to adequately generate data to feed machine learning algorithms that can prevent and diagnose health issues.
A. Estela Herguedas-Alonso +2 more
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Overcomplete Transform Learning With the
IEEE Access, 2018 Transform learning has been proposed as a new and effective formulation for analysis dictionary learning, where the ℓ0 norm or the ℓ1 norm are generally used as sparsity constraint.
Zhenni Li +3 more
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Image Denoising Using Hybrid Singular Value Thresholding Operators
IEEE Access, 2020 Truncated singular value decomposition (TSVD) is a simple and efficient technique for patch-based image denoising, in which a hard thresholding operator is utilized to set some small singular values to zero.
Fan Zhang +3 more
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Applied SciencesPartial discharge (PD) signals are used to evaluate the insulation condition of stators in electrical machines. Their measurements are often heavily corrupted by ambient noise, making denoising essential for effective detection and analysis of PD signals.
Dong Yang +4 more
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A Designed Thresholding Operator for Low-Rank Matrix Completion
MathematicsIn this paper, a new thresholding operator, namely, designed thresholding operator, is designed to recover the low-rank matrices. With the change of parameter in designed thresholding operator, the designed thresholding operator can apply less bias to ...
Angang Cui, Haizhen He, Hong Yang
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A Squared-Chebyshev wavelet thresholding based 1D signal compression
Defence Technology, 2019 In this paper a square wavelet thresholding method is proposed and evaluated as compared to the other classical wavelet thresholding methods (like soft and hard).
Hanan A.R. Akkar +2 more
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Soft thresholding for DCT speech enhancement
Electronics Letters, 2002 A speech enhancement method in the DCT domain using a new soft thresholding strategy is proposed. Exploiting the behaviour of the amplitude distribution of the DCT coefficients, a linear function is introduced for amplitude thresholding, unlike the conventional constant noise-level subtraction rule. The experimental results show significant improvement
S. Salahuddin +3 more
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Robust and Efficient Harmonics Denoising in Large Dataset Based on Random SVD and Soft Thresholding
IEEE Access, 2019 The Hankel matrix of harmonic signals has the important low-rank property, based on which the principal components (or the eigenvectors) extracted from the matrix by singular value decomposition (SVD) could be applied for harmonic signal denoising ...
Yu Yang, Jian Rao
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