Results 21 to 30 of about 13,919 (263)
Undersampled Windowed Exponentials and Their Applications [PDF]
Acta Applicandae Mathematicae, 2018 Referees comment incorporated, To appear in Acta.
Chun-Kit Lai, Sui Tang
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IEEE Access, 2023 The paper proposes an approach for mining imbalanced datasets combining specialized oversampling and undersampling methods. The oversampling part produces a set of non-dominated synthetic examples using two, possibly conflicting, criteria including ...
Joanna Jedrzejowicz, Piotr Jedrzejowicz
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Teknika, 2023 Technological developments in the automotive industry have experienced significant progress in recent years. Currently, many electric vehicles are being produced as an environmentally friendly alternative to vehicles.
Naufal Avilandi Poedjimartojo +2 more
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An Efficient CRT Based Algorithm for Frequency Determination from Undersampled Real Waveform
Sensors, 2023 The Chinese Remainder Theorem (CRT) based frequency estimation has been widely studied during the past two decades. It enables one to estimate frequencies by sub-Nyquist sampling rates, which reduces the cost of hardware in a sensor network.
Yao-Wen Zhang +2 more
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Undersampling Instance Selection for Hybrid and Incomplete Imbalanced Data [PDF]
Journal of Universal Computer Science, 2020 This paper proposes a novel undersampling method, for dealing with imbalanced datasets. The proposal is based on a novel instance importance measure (also introduced in this paper), and is able to balance hybrid and incomplete data.
Oscar Camacho-Nieto +2 more
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MPSUBoost: A Modified Particle Stacking Undersampling Boosting Method
IEEE Access, 2022 Class imbalance problems are prevalent in the real world. In such cases, traditional supervised algorithms tend to have difficulty in recognizing minority data because the models are likely to maximize prediction accuracy by simply ignoring minority data.
Sang-Jin Kim, Dong-Joon Lim
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Undersampling in Orthogonal Frequency Division Multiplexing Telecommunication Systems
Applied Sciences, 2014 Several techniques have been proposed that attempt to reconstruct a sparse signal from fewer samples than the ones required by the Nyquist theorem.
Nikos Petrellis
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Uncalibrated Distortions vs Undersampling
Vision Research, 1996 In a recent paper of ours [Hess & Field (1993). Vision Research, 33, 2663-2670], we claim that there was a predictable relationship between position errors and contrast errors for an undersampled system. In this paper we re-state our main points. We feel that the response to that paper by Levi and Klein in the accompanying article does not require us ...
FIELD, DAVID J, HESS, ROBERT F
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Beyond Nyquist: A Comparative Analysis of 3D Deep Learning Models Enhancing MRI Resolution
Journal of ImagingHigh-spatial resolution MRI produces abundant structural information, enabling highly accurate clinical diagnosis and image-guided therapeutics. However, the acquisition of high-spatial resolution MRI data typically can come at the expense of less ...
Soumick Chatterjee +10 more
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Applied Sciences, 2022 A covariance matrix is an important parameter in many computational applications, such as quantitative trading. Recently, a global minimum variance portfolio received great attention due to its performance after the 2007–2008 financial crisis, and this ...
Tuan Tran, Nhat Nguyen, Trung Nguyen
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