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Non-convex sparse optimization-based impact force identification with limited vibration measurements

Frontiers of Mechanical Engineering 2023, Volume 18, Issue 3, doi: 10.1007/s11465-023-0762-2

Abstract: Impact force identification is important for structure health monitoring especially in applications involvingDifferent from the traditional direct measurement method, the impact force identification technique ismn> regularization method often struggles to generate sparseTo alleviate such limitations, a novel non-convex sparse regularization method that uses the non-convexrealize simultaneous impact localization and time history reconstruction with an under-determined, sparse

Keywords： impact force identification     inverse problem     sparse regularization     under-determined condition     alternating    

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Asystematic review of structured sparse learning Review

Lin-bo QIAO, Bo-feng ZHANG, Jin-shu SU, Xi-cheng LU

Frontiers of Information Technology & Electronic Engineering 2017, Volume 18, Issue 4,   Pages 445-463 doi: 10.1631/FITEE.1601489

Abstract: from diverse scientific research fields and industrial development have led to increased interest in sparseStructured sparse learning encodes the structural information of the variables and has been quite successfulThese regularizations have greatly improved the efficacy of sparse learning algorithms through the useIn this article, we present a systematic review of structured sparse learning including ideas, formulationsimplementations, and compare the computational complexity of typical optimization methods to solve structured sparse

Keywords： Sparse learning     Structured sparse learning     Structured regularization    

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Sparse fast Clifford Fourier transform Article

Rui WANG, Yi-xuan ZHOU, Yan-liang JIN, Wen-ming CAO

Frontiers of Information Technology & Electronic Engineering 2017, Volume 18, Issue 8,   Pages 1131-1141 doi: 10.1631/FITEE.1500452

Abstract: The sparse fast Fourier transform (sFFT) theory deals with the big data problem by using input data selectivelyThis has inspired us to create a new algorithm called sparse fast CFT (SFCFT), which can greatly improve

Keywords： Sparse fast Fourier transform (sFFT)     Clifford Fourier transform (CFT)     Sparse fast Clifford Fourier    

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Multi-Objective Adaptive Optimization Model Predictive Control: Decreasing Carbon Emissions from a Zinc Oxide Rotary Kiln Article

Ke Wei, Keke Huang, Chunhua Yang, Weihua Gui

Engineering 2023, Volume 27, Issue 8,   Pages 96-105 doi: 10.1016/j.eng.2023.01.017

Abstract: proposes a multi-objective adaptive optimization model predictive control (MAO-MPC) method based on sparseidentification.More specifically, with a large amount of data collected from a CFD model, a sparse regression problem

Keywords： Zinc oxide rotary kiln     Model reduction     Sparse identification     Real-time optimization     Model predictive    

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Uncertainty propagation analysis by an extended sparse grid technique

X. Y. JIA, C. JIANG, C. M. FU, B. Y. NI, C. S. WANG, M. H. PING

Frontiers of Mechanical Engineering 2019, Volume 14, Issue 1,   Pages 33-46 doi: 10.1007/s11465-018-0514-x

Abstract: In this paper, an uncertainty propagation analysis method is developed based on an extended sparse gridSubsequently, within the sparse grid numerical integration framework, the statistical moments of the

Keywords： uncertainty propagation analysis     extended sparse grid     maximum entropy principle     extended Gauss integration    

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Laplacian sparse dictionary learning for image classification based on sparse representation Article

Fang LI, Jia SHENG, San-yuan ZHANG

Frontiers of Information Technology & Electronic Engineering 2017, Volume 18, Issue 11,   Pages 1795-1805 doi: 10.1631/FITEE.1600039

Abstract: Sparse representation is a mathematical model for data representation that has proved to be a powerfulAs one of the building blocks of the sparse representation method, dictionary learning plays an importantWe incorporate the Laplacian weighted graph in the sparse representation model and impose the l1-normAn LSD is a sparse overcomplete dictionary that can preserve the intrinsic structure of the data andResults show the advantages of the proposed LSD algorithm over state-of-the-art sparse representation

Keywords： Sparse representation     Laplacian regularizer     Dictionary learning     Double sparsity     Manifold    

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Home location inference from sparse and noisy data: models and applications

Tian-ran HU,Jie-bo LUO,Henry KAUTZ,Adam SADILEK

Frontiers of Information Technology & Electronic Engineering 2016, Volume 17, Issue 5,   Pages 389-402 doi: 10.1631/FITEE.1500385

Abstract: In particular, the sparse and noisy nature of social media data poses serious challenges in pinpointingknowledge, this is the first time home location has been detected at such a fine granularity using sparse

Keywords： Home location     Mobility patterns     Healthcare    

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Data-Driven Discovery of Stochastic Differential Equations Article

Yasen Wang, Huazhen Fang, Junyang Jin, Guijun Ma, Xin He, Xing Dai, Zuogong Yue, Cheng Cheng, Hai-Tao Zhang, Donglin Pu, Dongrui Wu, Ye Yuan, Jorge Gonçalves, Jürgen Kurths, Han Ding

Engineering 2022, Volume 17, Issue 10,   Pages 244-252 doi: 10.1016/j.eng.2022.02.007

Abstract: The identification of SDEs governing a system is often a challenge because of the inherent strong stochasticityThis study presents a novel framework for identifying SDEs by leveraging the sparse Bayesian learning

Keywords： Data-driven method     System identification     Sparse Bayesian learning     Stochastic differential equations    

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Variational mode decomposition based modal parameter identification in civil engineering

Mingjie ZHANG, Fuyou XU

Frontiers of Structural and Civil Engineering 2019, Volume 13, Issue 5,   Pages 1082-1094 doi: 10.1007/s11709-019-0537-3

Abstract: An out-put only modal parameter identification method based on variational mode decomposition (VMD) isThe proposed identification method can straightforwardly extract the mode shape vectors using the modaldemonstrate the efficiency and highlight the superiority of the proposed method in modal parameter identificationThe proposed method is proved to be efficient and accurate in modal parameter identification for both

Keywords： modal parameter identification     variational mode decomposition     civil structure     nonlinear system     closely    

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Robust object tracking with RGBD-based sparse learning Article

Zi-ang MA, Zhi-yu XIANG

Frontiers of Information Technology & Electronic Engineering 2017, Volume 18, Issue 7,   Pages 989-1001 doi: 10.1631/FITEE.1601338

Abstract: In this paper, a novel RGBD and sparse learning based tracker is proposed.The range data is integrated into the sparse learning framework in three respects.demonstrate that the proposed tracker outperforms the state-of-the-art tracking algorithms, including both sparse

Keywords： Object tracking     Sparse learning     Depth view     Occlusion templates     Occlusion detection    

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The research on structural damage identification using rough set and integrated neural network

Juelong LI, Hairui LI, Jianchun XING, Qiliang YANG

Frontiers of Mechanical Engineering 2013, Volume 8, Issue 3,   Pages 305-310 doi: 10.1007/s11465-013-0259-5

Abstract:

A huge amount of information and identification accuracy in large civil engineering structural damageidentification has not been addressed yet.To efficiently solve this problem, a new damage identification method based on rough set and integratedThe decision fusion network will give the final damage identification results.The identification examples show that this method can simplify the redundant information to reduce the

Keywords： rough set     integrated neural network     damage identification     decision making fusion    

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Unsupervised feature selection via joint local learning and group sparse regression Regular Papers

Yue WU, Can WANG, Yue-qing ZHANG, Jia-jun BU

Frontiers of Information Technology & Electronic Engineering 2019, Volume 20, Issue 4,   Pages 538-553 doi: 10.1631/FITEE.1700804

Abstract: issue, we propose a novel unsupervised feature selection algorithm via joint local learning and group sparseregression in a single formulation, and seeks features that respect both the manifold structure and group sparse

Keywords： Unsupervised     Local learning     Group sparse regression     Feature selection    

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Mechanical design, modeling, and identification for a novel antagonistic variable stiffness dexterous

Frontiers of Mechanical Engineering 2022, Volume 17, Issue 3, doi: 10.1007/s11465-022-0691-5

Abstract: Experimental results of the finger joint stiffness identification and finger impact tests under different

Keywords： multifingered hand     mechanism design     robot safety     variable stiffness actuator    

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Efficient scheme of low-dose CT reconstruction using TV minimization with an adaptive stopping strategy and sparse Article

Yong DING, Tuo HU

Frontiers of Information Technology & Electronic Engineering 2017, Volume 18, Issue 12,   Pages 2001-2008 doi: 10.1631/FITEE.1700287

Abstract: imaging, we propose a promising reconstruction scheme which combines total-variation minimization and sparse

Keywords： Low-dose computed tomography (CT)     CT imaging     Total variation     Sparse dictionary learning    

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Damage identification in connections of moment frames using time domain responses and an optimization

Frontiers of Structural and Civil Engineering 2021, Volume 15, Issue 4,   Pages 851-866 doi: 10.1007/s11709-021-0739-3

Abstract: In this study, an optimization-based method for joint damage identification of moment frames using theThen, the problem of joint damage identification is converted to a standard optimization problem.Then, a comparison between the proposed method and the existing damage identification method is provided

Keywords： damage identification     beam-to-column connection     time-domain response     optimization    

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Title Author Date Type Operation

Non-convex sparse optimization-based impact force identification with limited vibration measurements

Journal Article

Asystematic review of structured sparse learning

Lin-bo QIAO, Bo-feng ZHANG, Jin-shu SU, Xi-cheng LU

Journal Article

Sparse fast Clifford Fourier transform

Rui WANG, Yi-xuan ZHOU, Yan-liang JIN, Wen-ming CAO

Journal Article

Multi-Objective Adaptive Optimization Model Predictive Control: Decreasing Carbon Emissions from a Zinc Oxide Rotary Kiln

Ke Wei, Keke Huang, Chunhua Yang, Weihua Gui

Journal Article

Uncertainty propagation analysis by an extended sparse grid technique

X. Y. JIA, C. JIANG, C. M. FU, B. Y. NI, C. S. WANG, M. H. PING

Journal Article

Laplacian sparse dictionary learning for image classification based on sparse representation

Fang LI, Jia SHENG, San-yuan ZHANG

Journal Article

Home location inference from sparse and noisy data: models and applications

Tian-ran HU,Jie-bo LUO,Henry KAUTZ,Adam SADILEK

Journal Article

Data-Driven Discovery of Stochastic Differential Equations

Yasen Wang, Huazhen Fang, Junyang Jin, Guijun Ma, Xin He, Xing Dai, Zuogong Yue, Cheng Cheng, Hai-Tao Zhang, Donglin Pu, Dongrui Wu, Ye Yuan, Jorge Gonçalves, Jürgen Kurths, Han Ding

Journal Article

Variational mode decomposition based modal parameter identification in civil engineering

Mingjie ZHANG, Fuyou XU

Journal Article

Robust object tracking with RGBD-based sparse learning

Zi-ang MA, Zhi-yu XIANG

Journal Article

The research on structural damage identification using rough set and integrated neural network

Juelong LI, Hairui LI, Jianchun XING, Qiliang YANG

Journal Article

Unsupervised feature selection via joint local learning and group sparse regression

Yue WU, Can WANG, Yue-qing ZHANG, Jia-jun BU

Journal Article

Mechanical design, modeling, and identification for a novel antagonistic variable stiffness dexterous

Journal Article

Efficient scheme of low-dose CT reconstruction using TV minimization with an adaptive stopping strategy and sparse

Yong DING, Tuo HU

Journal Article

Damage identification in connections of moment frames using time domain responses and an optimization

Journal Article