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1
Universal Approximation Capability of Broad Learning System and Its Structural Variations
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Universal Approximation Capability of Broad Learning System and Its Structural Variations

Chen, C. L. Philip ; Liu, Zhulin ; Feng, Shuang

IEEE transaction on neural networks and learning systems, 2019-04, Vol.30 (4), p.1191-1204

United States: IEEE

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2
A mathematical model of healthy and dystrophic skeletal muscle biomechanics
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Artigo
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A mathematical model of healthy and dystrophic skeletal muscle biomechanics

Stefanati, Marco ; Villa, Chiara ; Torrente, Yvan ; Rodriguez Matas, José Félix

Journal of the mechanics and physics of solids, 2020-01, Vol.134, p.103747, Article 103747 [Periódico revisado por pares]

London: Elsevier Ltd

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3
Cardiovascular Function and Ballistocardiogram: A Relationship Interpreted via Mathematical Modeling
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Cardiovascular Function and Ballistocardiogram: A Relationship Interpreted via Mathematical Modeling

Guidoboni, Giovanna ; Sala, Lorenzo ; Enayati, Moein ; Sacco, Riccardo ; Szopos, Marcela ; Keller, James M ; Popescu, Mihail ; Despins, Laurel ; Huxley, Virginia H ; Skubic, Marjorie

IEEE transactions on biomedical engineering, 2019-10, Vol.66 (10), p.2906-2917 [Periódico revisado por pares]

United States: IEEE

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4
Early Prediction of the 2019 Novel Coronavirus Outbreak in the Mainland China Based on Simple Mathematical Model
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Early Prediction of the 2019 Novel Coronavirus Outbreak in the Mainland China Based on Simple Mathematical Model

Zhong, Linhao ; Mu, Lin ; Li, Jing ; Wang, Jiaying ; Yin, Zhe ; Liu, Darong

IEEE access, 2020-01, Vol.8, p.51761-51769 [Periódico revisado por pares]

United States: IEEE

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5
A Novel Empirical Mode Decomposition With Support Vector Regression for Wind Speed Forecasting
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A Novel Empirical Mode Decomposition With Support Vector Regression for Wind Speed Forecasting

Ye Ren ; Suganthan, Ponnuthurai Nagaratnam ; Srikanth, Narasimalu

IEEE transaction on neural networks and learning systems, 2016-08, Vol.27 (8), p.1793-1798

United States: IEEE

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6
Projected Iterative Soft-Thresholding Algorithm for Tight Frames in Compressed Sensing Magnetic Resonance Imaging
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Projected Iterative Soft-Thresholding Algorithm for Tight Frames in Compressed Sensing Magnetic Resonance Imaging

Liu, Yunsong ; Zhan, Zhifang ; Cai, Jian-Feng ; Guo, Di ; Chen, Zhong ; Qu, Xiaobo

IEEE transactions on medical imaging, 2016-09, Vol.35 (9), p.2130-2140

United States: IEEE

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7
Black-Box vs. White-Box: Understanding Their Advantages and Weaknesses From a Practical Point of View
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Black-Box vs. White-Box: Understanding Their Advantages and Weaknesses From a Practical Point of View

Loyola-Gonzalez, Octavio

IEEE access, 2019, Vol.7, p.154096-154113 [Periódico revisado por pares]

Piscataway: IEEE

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8
A Survey on Mathematical, Machine Learning and Deep Learning Models for COVID-19 Transmission and Diagnosis
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Artigo
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A Survey on Mathematical, Machine Learning and Deep Learning Models for COVID-19 Transmission and Diagnosis

John, Christopher Clement ; Ponnusamy, VijayaKumar ; Krishnan Chandrasekaran, Sriharipriya ; R, Nandakumar

IEEE reviews in biomedical engineering, 2022-01, Vol.15, p.325-340 [Periódico revisado por pares]

United States: IEEE

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9
SVD Compression for Magnetic Resonance Fingerprinting in the Time Domain
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SVD Compression for Magnetic Resonance Fingerprinting in the Time Domain

McGivney, Debra F. ; Pierre, Eric ; Dan Ma ; Yun Jiang ; Saybasili, Haris ; Gulani, Vikas ; Griswold, Mark A.

IEEE transactions on medical imaging, 2014-12, Vol.33 (12), p.2311-2322

United States: IEEE

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10
Actor-Critic-Based Optimal Tracking for Partially Unknown Nonlinear Discrete-Time Systems
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Actor-Critic-Based Optimal Tracking for Partially Unknown Nonlinear Discrete-Time Systems

Kiumarsi, Bahare ; Lewis, Frank L.

IEEE transaction on neural networks and learning systems, 2015-01, Vol.26 (1), p.140-151

United States: IEEE

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