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2024 China automation Congress, CAC 2024

作者： Huang, Yuan Xu, Chi School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China

ISBN: (纸本)9798350368604

Recent advancements in Novel View Synthesis using neural radiance fields and 3D Gaussian splatting have demonstrated promising results. However, these methods conventionally rely on accurate initial poses and point clouds from the model of structure from motion, which poses challenges in sparse input views. To addressing these drawbacks, we introduces an novel method for view synthesis based on 3D Gaussian splatting. Our approach operates on sparse input views without the prerequisite of pose priors, achieving reconstruction and real-time rendering of novel perspectives. For the deficiency of camera poses and point cloud, we employ an end-to-end deep learning model to recover the 3D structure from a few of 2D images to initialize the 3D Gaussian point cloud. In addressing the issue with few-shot, we utilize the differentiable rasterization module to render depth map and apply regulation on it. Additionally, we incorporate supervision between input views by interpolating to generate novel perspectives during training. Experimental results demonstrate that our proposed method significantly enhances the capabilities of 3D Gaussian splatting for novel view synthesis in sparse views and without the necessity of camera pose priors. © 2024 IEEE.

关键词： 3D reconstruction

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Design of Load Frequency controller for Power system Based on Equivalent Input Disturbance Method 4

Design of Load Frequency Controller for Power System Based o...

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4th IEEE New Energy and Energy Storage system control Summit Forum, NEESSC 2024

作者： Zhang, Jianrong Xu, Hang Wang, Hongzhang Zhang, Chuanke China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education School of Automation Wuhan China

ISBN: (纸本)9798350389012

In the power system, due to the instability of the external environment, safe and stable operation cannot always be guaranteed, as it frequently encounters varying degrees of external disturbances. In order to mitigate the effects of these disturbances on the system, the power system can operate safely and stably, In this paper, a power system load frequency control (LFC) based on Equivalent Input Disturbance (EID) method is proposed from the perspective of active disturbance suppression. Firstly, the disturbances present in the environment are unified as external disturbances, and then a single area the electric power system model with external disturbance was constructed. Then, a controller algorithm based on EID was designed using EID equivalent processing method and linear matrix inequality method to address the issue of external interference in the power system. Finally, a numerical example is used to validate the effectiveness and accuracy of the controller by simulating with two aspects, fixed perturbation and random perturbation, respectively. © 2024 IEEE.

关键词： Linear matrix inequalities

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Fault Detection of a 6-DOF Hydraulic Platform Based on Equivalent-Input-Disturbance Approach 29

Fault Detection of a 6-DOF Hydraulic Platform Based on Equiv...

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第29届中国控制与决策会议

作者： Qianqiu Li Jinhua She Min Wu Pingping Lin School of Information Science and Engineering Central South University School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems School of Engineering Tokyo University of Technology

ISBN: (纸本)9781509046584

This paper presents a method of fault detection for a 6-degree-of-freedom hydraulic platform based on the equivalent-input-disturbance(EID) ***,a model of the platform is derived based on the Lagrange ***,the types of actuator faults are ***,an optimal feedback controller is designed and the EID approach is incorporated to detect and suppress actuator *** results demonstrate the effectiveness of the method.

关键词： Equivalent input disturbance 6 degrees of freedom Fault detection Optimal feedback controller

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Spectral gap, isoperimetry and concentration on trees

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Science China Mathematics 2016年第3期59卷 539-556页

作者： LIU Wei MA Yu Tao WU Li Ming School of Mathematics and Statistics Wuhan University Computational Science Hubei Key Laboratory Wuhan University School of Mathematical Sciences & Laboratory of Complex System and Intelligent Control Beijing Normal University Laboratoire de Mathematics Université Blaise Pascal

We consider the nearest-neighbor model on the finite tree T with generator L. We obtain a twosided estimate of the spectral gap by factor 2. We also identify explicitly the Lipschitzian norm of the operator(-L)^(-1) in propriate functional space. This leads to the identification of the best constant in the generalized Cheeger isoperimetric inequality on the tree, and to transportation-information inequalities.

关键词： tree nearest-neighbor model Poisson equation transportation-information inequality concentration inequality Cheeger-type isoperimetric inequality

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Decoupling control for Parallel Robot Based on Equivalent-Input-Disturbance Approach 29

Decoupling Control for Parallel Robot Based on Equivalent-In...

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第29届中国控制与决策会议

作者： Pingping Lin Jinhua She Min Wu Qianqiu Li School of Information Science and Engineering Central South University School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems School of Engineering Tokyo University of Technology

ISBN: (纸本)9781509046584

This paper discusses the problem of posture control for a parallel *** parallel robot features multiple variables and large *** control accuracy is strongly affected by the parameters which are coupled with each other,and by exogenous disturbances.A decoupling control strategy is presented based on the equivalent-inputdisturbance(EID) approach to improve control ***,decoupling control is used to eliminate the main coupling effect between multiple ***,the EID method is used to further improve decoupling effect and suppress the external *** results show that the control strategy is effective for the decoupling control of parallel robot.

关键词： Parallel Robot Decoupling control Equivalent Input Disturbance(EID) PID

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CDP-GAN:Near-Infrared and Visible Image Fusion Via Color Distribution Preserved GAN

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IEEE/CAA Journal of Automatica Sinica 2022年第9期9卷 1698-1701页

作者： Jun Chen Kangle Wu Yang Yu Linbo Luo the School of Automation Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex SystemsEngineering Research Center of Intelligent Technology for Geo-ExplorationMinistry of EducationChina University of GeosciencesWuhan 430074China the Shanghai Institute of Technical Physics Key Laboratory of Infrared System Detecting and Imaging TechnologyChinese Academy of SciencesShanghai 200083China the School of Mechanical Engineering and Electronic Information China University of GeosciencesWuhan 430074China

Dear Editor,This letter is concerned with dealing with the great discrepancy between near-infrared(NIR)and visible(VS)image fusion via color distribution preserved generative adversarial network(CDP-GAN).Different from the global discriminator in prior GAN,conflict of preserving NIR details and VS color is resolved by introducing an attention guidance mechanism into the ***。

关键词： details dealing preserving

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Modeling for coke quality prediction using Gaussian function and SGA

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Science China(Information Sciences) 2022年第1期65卷 282-284页

作者： Yan YUAN Qilin QU Weihua CAO Min WU School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

Dear editor,Recently, we made some new attempts at predicting coke quality. Coke quality prediction provides important guidance for coal blending, improving the quality of coke, and reducing the cost. Prediction usually involves selection of the coal blending parameters and selection of the modeling methods. In recent years, traditional coal quality indicators such as coal impurity(ash Ad, sulfur St.d),

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GCN-Transformer Autoencoder with Knowledge Distillation for Unsupervised Video Anomaly Detection

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Journal of advanced Computational Intelligence and intelligent Informatics 2025年第3期29卷 659-667页

作者： Yan, Mingchao Xiong, Yonghua She, Jinhua School of Automation China University of Geosciences No.388 Lumo Road Hongshan District Hubei Wuhan 430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems No.388 Lumo Road Hongshan District Hubei Wuhan 430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education No.388 Lumo Road Hongshan District Hubei Wuhan 430074 China School of Engineering Tokyo University of Technology 1404-1 Katakura Hachioji Tokyo 192-0982 Japan

Video anomaly detection is crucial in intelligent surveillance, yet the scarcity and diversity of abnormal events pose significant challenges for supervised methods. This paper presents an unsupervised framework that integrates graph attention networks (GATs) and Transformer architectures, combining masked autoencoders (MAEs) with self-distillation training. GATs are utilized to model spatial and inter-frame relationships, while Transformers capture long-range temporal dependencies, overcoming the limitations of traditional MAE and self-distillation approaches. The model employs a two-stage training process: first, a lightweight MAE combined with a GAT-Transformer fusion constructs a knowledge distillation module;second, the student autoencoder is optimized by integrating a graph convolutional autoencoder and a classification head to identify synthetic anomalies. We evaluate the proposed method on three representative datasets—ShanghaiTech Campus, UBnormal, and UCSD Ped2—and achieve promising results. © Fuji Technology Press Ltd.

关键词： GAT-Transformer fusion graph convolutional networks knowledge distillation self-distillation video anomaly detection

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Variational Autoencoder Based Network Embedding Algorithm for Protein Function Prediction 2022

Variational Autoencoder Based Network Embedding Algorithm fo...

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14th International Conference on Machine Learning and Computing, ICMLC 2022

作者： Cao, Guansong Zhu, Yuan Yi, Ming School of Automation China University of Geosciences China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex System China University of Geosciences Wuhan China School of Mathematics and Physics China University of Geosciences Wuhan China

ISBN: (纸本)9781450395700

The development of high-throughput technology has produced a large number of protein-protein interaction datasets, which provide an effective way to infer the functional annotation of proteins. However, how to make proper use of these datasets to extract effective low-dimensional feature representation of proteins for functional prediction is a challenge. Most existing network integration methods for protein function prediction have some limitations to capture complex and highly non-linear network structure information due to their design architecture. Therefore, we propose a novel multi-network embedding method deepVAE based on deep variational autoencoder (VAE), which uses the variational autoencoder to extract low-dimensional features of proteins from multiple various interactive network datasets and then trains a SVM classifier to predict protein function. Particularly, we denoise the original networks before network embedding, thus the new proposed method is called deepVAE-NE. The experiments are conducted on the yeast and human protein-protein interaction datasets and the experimental performance shows that our methods perform better than the other four compared advanced approaches, which greatly improves the accuracy of functional prediction. © 2022 ACM.

关键词： Proteins

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Bifurcation control and circuit simulation of a fractional-order synthetic gene networks 41

Bifurcation control and circuit simulation of a fractional-o...

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第41届中国控制会议

作者： Feng Liu Feiyue Zhuo Shujiang Sun Zhi-Hong Guan Hua O Wang School of Automation China University of Geosciences Engineering Research Center of Ministry of education for intelligent technology of earth exploration Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems School of Artificial Intelligence and Automation Department of Mechanical Engineering Boston University

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

This paper presents a ring synthetic gene network model described by fractional differential equations,studies the conditions of Hopf bifurcation in the model,and discusses the limit cycle oscillation phenomenon due to the existence of bifurcation,which causes the system to become unstable,and then We propose a method to control the bifurcation behavior in the system,so that the system can be stable over a large *** addition,the dynamic behavior of the fractional-order model is simulated by triggering a genetic oscillator(a single inhibitory gene) composed of a transistor composed of linear and nonlinear electronic *** circuit simulation results well verify the theoretical analysis conclusion,and the circuit simulation model can well demonstrate the biological characteristics of gene regulatory networks.

关键词： Synthetic gene networks fractional-order bifurcation control circuit simulation

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