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121 results on '"Hu, Chunhai"'

1. Decomposition Method for Lipschitz Stability of General LASSO-type Problems

Author

Hu, Chunhai, Yao, Wei, and Zhang, Jin

Subjects
Mathematics - Optimization and Control
Abstract

This paper introduces a decomposition-based method to investigate the Lipschitz stability of solution mappings for general LASSO-type problems with convex data fidelity and $\ell_1$-regularization terms. The solution mappings are considered as set-valued mappings of the measurement vector and the regularization parameter. Based on the proposed method, we provide two regularity conditions for Lipschitz stability: the weak and strong conditions. The weak condition implies the Lipschitz continuity of solution mapping at the point in question, regardless of solution uniqueness. The strong condition yields the local single-valued and Lipschitz continuity of solution mapping. When applied to the LASSO and Square Root LASSO (SR-LASSO), the weak condition is new, while the strong condition is equivalent to some sufficient conditions for Lipschitz stability found in the literature. Specifically, our results reveal that the solution mapping of the LASSO is globally (Hausdorff) Lipschitz continuous without any assumptions. In contrast, the solution mapping of the SR-LASSO is not always Lipschitz continuous. A sufficient and necessary condition is proposed for its local Lipschitz property. Furthermore, we fully characterize the local single-valued and Lipschitz continuity of solution mappings for both problems using the strong condition., Comment: 31 pages

Published
2024

3. State of Health Estimation of Lithium-Ion Batteries via Electrochemical Impedance Spectroscopy and Machine Learning

Author

Liu, Shiyu, Wang, Shutao, Hu, Chunhai, Zhao, Xiaoyu, Gu, Fengshou, IFToMM, Series Editor, Ceccarelli, Marco, Advisory Editor, Corves, Burkhard, Advisory Editor, Glazunov, Victor, Advisory Editor, Hernández, Alfonso, Advisory Editor, Huang, Tian, Advisory Editor, Jauregui Correa, Juan Carlos, Advisory Editor, Takeda, Yukio, Advisory Editor, Agrawal, Sunil K., Advisory Editor, Ball, Andrew D., editor, Ouyang, Huajiang, editor, Sinha, Jyoti K., editor, and Wang, Zuolu, editor

Published
2024
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10. Markov Transform Field Coupled with CNN Image Analysis Technology in NIR Detection of Alcohols Diesel

Author

Liu, Shiyu, Wang, Shutao, Hu, Chunhai, Kong, Deming, Ceccarelli, Marco, Series Editor, Agrawal, Sunil K., Advisory Editor, Corves, Burkhard, Advisory Editor, Glazunov, Victor, Advisory Editor, Hernández, Alfonso, Advisory Editor, Huang, Tian, Advisory Editor, Jauregui Correa, Juan Carlos, Advisory Editor, Takeda, Yukio, Advisory Editor, Zhang, Hao, editor, Ji, Yongjian, editor, Liu, Tongtong, editor, Sun, Xiuquan, editor, and Ball, Andrew David, editor

Published
2023
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27. Convolutional neural networks driving thermally enhanced upconversion luminescence for temperature sensing: achieving high accuracy and robustness across a wide temperature range.

Author

Xu, Wei, Cui, Junqi, Bai, Fengze, Zheng, Longjiang, Hu, Chunhai, Zhang, Zhiguo, Sun, Zhen, and Zhang, Yungang

Abstract

The accuracy of luminescence thermometry is seriously hindered by thermal-induced luminescence quenching as well as traditional single spectral parameter-based analytical methods, which rely on subjective experience of humans and fail to effectively utilize the spectral features. Herein, thermally intensified luminescence of Cr3+ is successfully achieved in Gd3Ga5O12:Yb3+–Er3+–Cr3+ under 980 nm laser excitation and about 10-fold enhancement is observed at 853 K compared with that at 303 K. The reabsorption of Er3+ luminescence by Cr3+ and the phonon-assisted energy transfer from Er3+ to Cr3+ are responsible for the Cr3+ luminescence, and the latter is the key to the enhanced luminescence, which guarantees good signal-to-noise ratio of emissions at high temperatures. A convolutional neural network (CNN) is subsequently proposed to extract thermal information from the UC (upconversion) emissions, and the maximum error is just about 0.63 K in the temperature range of 303–853 K, along with an average error of only 0.15 K, much better than those obtained with conventional ratiometric approaches. Additionally, luminescence thermometry driven by CNNs can effectively resist the interference of background light and ensure measurement accuracy, further demonstrating the excellent robustness of the proposed thermometry strategy. [ABSTRACT FROM AUTHOR]

Published
2023
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35. Lagrange multiplier rules for weak approximate Pareto solutions to constrained vector optimization problems with variable ordering structures.

Author

Hu, Chunhai and Zhu, Jiangxing

Subjects
*CONSTRAINED optimization, *LAGRANGE multiplier, *SUBDIFFERENTIALS, *CONES
Abstract

In this paper, we consider the weak approximate solutions to constrained vector optimization problems with variable ordering structures. In terms of abstract subdifferentials, normal cones and coderivatives, we establish Lagrange rules for this kind of solutions. [ABSTRACT FROM AUTHOR]

Published
2022
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42. Visual Attention-Driven Geodesic Active Contour Model and Its Application

Author

刘斌 Liu Bin and 胡春海 Hu Chunhai

Subjects
Geodesic active contour model, business.industry, Computer science, Visual attention, Computer vision, Artificial intelligence, business, Atomic and Molecular Physics, and Optics, Electronic, Optical and Magnetic Materials
Published
2010

46. Calculation Method of Relative Illumination of Lens Image Plane

Author

刘宵婵 Liu Xiao-chan, 胡春海 Hu Chunhai, 李维善 Li Wei-shan, 陈琛 Chen Chen, and 宋涛 Song Tao

Subjects
Physics, business.industry, Phase telescope, 02 engineering and technology, Image plane, 021001 nanoscience & nanotechnology, 01 natural sciences, Atomic and Molecular Physics, and Optics, Electronic, Optical and Magnetic Materials, law.invention, Critical illumination, 010309 optics, Lens (optics), Optics, law, 0103 physical sciences, Köhler illumination, Cylindrical lens, 0210 nano-technology, business
Published
2016

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