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检索条件"机构=Hubei Key Laboratory of Advanced Control and Intelligent Automation fo Complex Systems"

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Staff lines Detection and Removal for Camera-Based Music Scores

Staff lines Detection and Removal for Camera-Based Music Sco...

引用

第37届中国控制会议

作者： Zhe Xiao Xin Chen Fang Wang School of Automation China University of Geoscience Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

Musical staff lines detection and removal, the first step of most Optical Music Recognition（OMR） technology, aims to detect staff positions and segment score image by removing those staff lines. To deal with issues that the disappearance of thin staff lines in the captured score image, line repaired algorithm based on music rules is proposed in this paper. It first estimates two reference lengths, staff width and space between two adjacent lines. Then projection is used to obtain potential staves *** least the staves are finally determined based on line repaired algorithm, the missing lines repaired and the redundant lines deleted at the same time. The proposed technique is simple and effective, making full use of global information of the musical scores. Experimental results show that our method achieves impressive results on music score images captured from cameras.

关键词： OMR staff lines detection staff removal run-length optical character recognition

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A New Result on H∞ State Estimation of Delayed Static Neural Networks via Augmented Lyapunov-Krasovskii Functional

A New Result on H∞ State Estimation of Delayed Static Neura...

引用

第37届中国控制会议

作者： Zhenman Gao Yong He School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

In this paper,the problem on guaranteed H∞ performance state estimation for static neural networks with a timevarying delay is investigated and the corresponding criterion is ***,a novel augmented Lyapunov-Krasovskii functional(LKF) is *** the derivative of the LKF is estimated by the relaxed integral ***,the state estimator can be calculated by solving a set of linear matrix ***,an example is used to illustrate the effectiveness of the proposed method.

关键词： Static neural networks H∞ performance state estimation time-varying delay augmented LKF

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Research on Image Denoising Method Based on Wavelet Transform

Research on Image Denoising Method Based on Wavelet Transfor...

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第37届中国控制会议

作者： JunLei Song MeiJuan Chen Chang Jiang YanXia Huang Qi Liu Yuan Meng WenQin Mo KaiFeng Dong Fang Jin School of Automation China University of Geosciences Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

In the process of image acquisition and transmission, the image always generates noise due to internal and external interference. Noise reduces the quality of the image, and makes it difficult for subsequent image processing. Therefore, image denoising is very important in image processing. Wavelet denoising can effectively filter out noise and retain high-frequency information of the image, this method has the characteristics of fast operation speed and has become an important branch of image denoising. Threshold functions commonly used in wavelet threshold denoising include hard threshold function and soft threshold function. The hard threshold function is not continuous as a whole. Although the soft threshold function has good continuity, there is always a constant deviation between the processed coefficient and the original coefficient when the wavelet coefficient is large. In response to these deficiencies, this paper establishes a new improved threshold function based on traditional soft and hard threshold functions. By processing the thresholds of wavelet coefficients, a reasonable balance between smoothing and edge oscillations can be achieved after image denoising. The improved threshold function not only overcomes the shortcomings of the soft and hard threshold functions, but also provides more flexibility in the processing of image *** MATLAB simulation, the denoising effects of the soft, hard threshold functions and the threshold function constructed in this paper are compared in terms of signal-to-noise ratio（SNR） and root mean square error（MSE）. The MATLAB simulation results show that compared with the traditional threshold function, the improved threshold function has a higher signal-to-noise ratio（SNR = 26.27709） and a smaller mean square error（MSE = 153.4579）, and it has a good noise reduction effect.

关键词： Wavelet threshold denoising Image denoising Wavelet transform Threshold function

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Stable control of Single-Link Flexible-Joint Manipulator

Stable Control of Single-Link Flexible-Joint Manipulator

引用

第37届中国控制会议

作者： Ze Yan Xuzhi Lai Qingxin Meng School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

This paper presents a novel approach for stable control of a single-link flexible-joint manipulator（SLFJM）.The control objective is to stabilize the SLFJM at the straight-up equilibrium position from the straight-down equilibrium position and suppress vibration by only using position ***,differential homeomorphic transformation is used to equivalently convert the original system into a new handy ***,the new system is divided into two parts: linear and *** nonlinear part is considered as a virtual disturbance of the linear ***,the Equivalent-input-disturbance-based（EID-based）control system is designed to suppress this virtual nonlinear disturbance at the zero equilibrium *** this way,the control objective of the original system is effectively ***,the numerical results demonstrate its validity.

关键词： Flexible-joint manipulator Equivalent-input-disturbance Global asymptotical stabilization Underactuated system

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Position control of a Planar four-Link Underactuated Manipulator

Position Control of a Planar Four-Link Underactuated Manipul...

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第37届中国控制会议

作者： Dong Liu Xuzhi Lai Yawu Wang Xiongbo Wan School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

A position control strategy by employing the model reduction and the cascade transformation is proposed for a planar four-link AAPA(Active-Active-Passive-Active) underactuated manipulator in this ***,a dynamics model of the system is ***,three controllers are designed based on the Lyapunov function to control the fourth active link from any initial angle to zero while the angles of the first and second active link remain their initial values,which makes the system is reduced to a planar virtual three-link AAP(Active-Active-Passive) underactuated ***,we obtain the new inputs of the cascade system of the planar virtual three-link AAP underactuated ***,we can get the controllers of the active links to realize the system position control *** results demonstrate the validity of the proposed control strategy.

关键词： Position control Model Reduction Cascade Transformation Underactuated Manipulator Lyapunov Function

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A Prediction Model Based on SVR for Untwist Angle in Drilling Process

A Prediction Model Based on SVR for Untwist Angle in Drillin...

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第37届中国控制会议

作者： Dian Zhang Min Wu Luefeng Chen School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

As slide steering technology has lower maintenance costs, it is widely used in geological drilling industry. In order to adjust the hole trajectory, this technology changes the drilling direction by controlling tool face angle of downhole power drill tool. However, due to the existence of the untwist angle, it is difficult to precisely control the angle, which will directly affect the quality of hole trajectory. So untwist angle prediction is the prerequisite of hole trajectory control. This paper introduces a common method for calculating untwist angle for generating the training set. And then factors that influence untwist angle will be analyzed. Meanwhile, based on the analysis and calculation results, support vector regression is introduced in the prediction algorithm to provide a new way for untwist angle prediction.

关键词： Downhole Drill Tool Bole Trajectory control Untwist Angle Support Vector Regression

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A Demand Analysis Method Based on TAKAGI-SUGENO Fuzzy Model for Drinking Service

A Demand Analysis Method Based on TAKAGI-SUGENO Fuzzy Model ...

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第37届中国控制会议

作者： Man Hao Weihua Cao Zhentao Liu School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

A demand analysis method based on TAKAGI-SUGENO（T-S） fuzzy model for drinking service is proposed to provide corresponding services according to users’ emotions and intentions in human-robot interaction,in which T-S fuzzy model is used to establish the relationship among human intention and human ***,the transformation of input and output is ***,fuzzy rules are formulated,and then fuzzy inference is applied to get user’s demand corresponding to emotion and *** proposal considers peoples fuzziness in inferring humans intention,which could help the robots to provide satisfied drinking service to *** validate the proposal,drinking service experiments are performed in a laboratory scenario using a humans-robots interaction system,from which the experimental results demonstrate the feasibility of the proposal.

关键词： Demand Analysis TAKAGI-SUGENO Model Drinking Service Human-Robot Interaction

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Tattoo Recognition Based on Triplet GAN

Tattoo Recognition Based on Triplet GAN

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第37届中国控制会议

作者： Cao Jiawang Zhu Yuan School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

An important feature of the deep learning algorithm is that the hidden layer of the neural network is more dependent on more computing resources and a larger amount of data. In this paper, we use Triplet GAN method to identify human body images with tattoos using fewer data sample labels. The model achieved better results（0.9462） than the only Triplet（0.8352） and only GAN（0.9178） in the MNIST dataset, it also achieved higher recognition accuracy（77-82%） under the premise of saving the amount of data, compared with the traditional machine learning algorithm（54-84%）. We provide a new idea for tattoo image recognition applications in embedded computing units.

关键词： Tattoo Recognition Triplet GAN Embedded Computing Units

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Dissipativity Analysis for Markovian Jump Neural Networks With Time-Varying Delay via An Extended Relaxed Integral Inequality

Dissipativity Analysis for Markovian Jump Neural Networks Wi...

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第37届中国控制会议

作者： LIN Wen-Juan HE Yong School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

This paper investigates the problem of the strictly(Q,S,R)-γ-dissipativity analysis for Markovian jump neural networks with a time-varying *** employing an appropriate Lyapunov-Krasovskii functional and using the extended relaxed integral inequality to estimate its derivative,a delay-dependent and mode-dependent condition that guarantee the considered Markovian jump neural networks strictly(Q,S,R)-γ-dissipative is ***,a numerical example is provided to illustrate the effectiveness of the proposed method.

关键词： Neural networks (Q,S,R)-γ-dissipativity Lyapunov-Krasovskii functional Extended relaxed integral inequality

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Identification of Essential Proteins Using Improved Node and Edge Clustering Coefficient

Identification of Essential Proteins Using Improved Node and...

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第37届中国控制会议

作者： Zhu Yuan Wu Chong School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

Computational methods are often applied to identify essential proteins from protein-protein interaction networks. In this paper, inspected by node and edge clustering coefficient（NEC） and Pe C, we propose an improved version of node and edge clustering coefficient（INEC） which both considers dual topological characteristics of the network and high false positives of the protein-protein interaction data. We apply it for the identification of essential proteins. And we implement three versions of INEC which combine different biological information. In order not to be confused, we call the first one INEC0 which dosen’t integrate biological information, the second one INEC1 which integrates gene expression similarity, and the third one INEC2 which integrates gene expression similarity, functional similarity, and protein-protein sequence similarity. We apply three implemented INEC methods to protein-protein interaction data of Saccharomyces cerevisiae（Yeast） and compare them with some state-of-theart methods（DC, NC, Pe C, and NEC）. The experimental results show that our proposed methods achieve better results in terms of prediction accuracy, area under the curve of PR-curve, and Jackknife methodology.

关键词： Protein-Protein Interaction Essential Protein Protein-Protein Interaction Network Biological Information

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