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第三十二届中国控制会议

作者： ZHANG Jishi Wu Yan WANG Yanwu GAO Zhonghu School of Automation Huazhong University of Science and Technology Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China Wuhan Institute of Marine Electric Propulsion CSIC

ISBN: (纸本)9781479900305

This paper addresses the stability and stabilization problems for a class of positive linear systems in the presence of saturating *** objective is to give conditions of the stability,and design state feedback control laws such that the closed-loop systems is asymptotically stable and positive at the origin with a large domain of *** sufficient conditions for stabilization and positivity are derived via the Lyapunov functions method and convex analysis in both the continuous-time and the discrete-time cases,*** state feedback controller design and the estimation of domain of attraction are presented by solving a convex optimization problem with LMIs constraints.A numerical example is given to show the effectiveness of the proposed methods.

关键词： Actuator Saturation Stability Analysis Positive System Domain of Attraction

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Demand-Side Frequency control in Power Network Based on Multi-Agent Deep Reinforcement Learning 5

Demand-Side Frequency Control in Power Network Based on Mult...

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5th International Conference on Industrial Artificial Intelligence, IAI 2023

作者： Liu, Xianggang Liu, Zhi-Wei Chi, Ming Zhang, Yifan Huazhong University of Science and Technology Key Laboratory of Image Processing and Intelligent Control Ministry of Education College of Artificial Intelligence and Automation Wuhan China

ISBN: (纸本)9798350325294

The integration of renewable energy sources into the power grid has led to new challenges in maintaining the stability of the system frequency. This paper proposes a novel approach to address the Optimal Demand Side Frequency control (ODFC) problem using Multi-Agent Deep Deterministic Policy Gradient (MADDPG) method. The proposed method models the ODFC problem as a Markov game, with centralized training based on multi-agent cooperative self-learning and associative storage service. In the decentralized execution stage, each agent independently outputs control actions to the controlled plant using local observations. Numerical simulations show that the proposed method effectively addresses the ODFC problem with superior performance compared to traditional methods. © 2023 IEEE.

关键词： Numerical methods

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EMPIRICAL STUDIES ON THE PROPERTIES OF LINEAR REGIONS IN DEEP NEURAL NETWORKS 8

EMPIRICAL STUDIES ON THE PROPERTIES OF LINEAR REGIONS IN DEE...

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8th International Conference on Learning Representations, ICLR 2020

作者： Zhang, Xiao Wu, Dongrui Ministry of Education Key Laboratory of Image Processing and Intelligent Control School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan China

A deep neural network (DNN) with piecewise linear activations can partition the input space into numerous small linear regions, where different linear functions are fitted. It is believed that the number of these regions represents the expressivity of the DNN. This paper provides a novel and meticulous perspective to look into DNNs: Instead of just counting the number of the linear regions, we study their local properties, such as the inspheres, the directions of the corresponding hyperplanes, the decision boundaries, and the relevance of the surrounding regions. We empirically observed that different optimization techniques lead to completely different linear regions, even though they result in similar classification accuracies. We hope our study can inspire the design of novel optimization techniques, and help discover and analyze the behaviors of DNNs. © 2020 8th International Conference on Learning Representations, ICLR 2020. All rights reserved.

关键词： Deep neural networks

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Graph-based scale-aware network for human parsing 1

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2nd Chinese Conference on Pattern Recognition and Computer Vision, PRCV 2019

作者： Yang, Beibei Yu, Changqian Liu, Jiahui Gao, Changxin Sang, Nong Key Laboratory of Ministry of Education for Image Processing and Intelligent Control School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan China

ISBN: (数字)9783030317232

ISBN: (纸本)9783030317225

Recent work has made considerable progress in exploring contextual information for human parsing with the Fully Convolutional Network framework. However, there still exist two challenges: (1) inherent relative relationships between parts;(2) scale variation of human parts. To tackle both problems, we propose a Graph-Based Scale-Aware Network for human parsing. First, we embed a Graph-Based Part Reasoning Layer into the backbone network to reason the relative relationship between human parts. Then we construct a Scale-Aware Context Embedding Layer, which consists of two branches to capture scale-specific contextual information, with different receptive fields and scale-specific supervisions. In addition, we adopt an edge supervision to further improve the performance. Extensive experimental evaluations demonstrate that the proposed model performs favorably against the state-of-the-art human parsing methods. More specifically, our algorithm achieves 53.32% (mIoU) on the LIP dataset. © Springer Nature Switzerland AG 2019.

关键词： Embeddings

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Bimodal Feature Propagation and Fusion for Real-time Semantic Segmentation on RGB-D images 7

Bimodal Feature Propagation and Fusion for Real-time Semanti...

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7th International Conference on intelligent Computing and Signal processing, ICSP 2022

作者： He, Ying Xiao, Li Sun, Zhigang Wang, Zhuo Huazhong University of Science and Technology Key Laboratory of Image Processing and Intelligent Control Ministry of Education School of Artificial Intelligence and Automation Wuhan China

ISBN: (纸本)9781665478571

Semantic Segmentation is the foundation of scene understanding and automatic driving tasks. One of the challenges of semantic segmentation is the reduction of feature resolution as the network goes deep. In this paper, the low-resolution features are integrated into high-resolution features progressively, enabling high-resolution prediction. Currently, incorporating the auxiliary depth information into a semantic segmentation framework has proven to be helpful to improve accuracy. However, additional process of depth data immensely increases computational complexity, resulting in limitation for practical application. Here, a real-time bimodal semantic segmentation network that effectively extracts and fuses complementary information is investigated. Our network extends a light-weight architecture which can seamlessly take advantage of various prevalent backbone networks. Our model extracts RGB and depth features from two branches in parallel and integrates multi-level features of two modalities through bimodal feature fusion blocks. To reduce computation complexity, we employ depth-wise separable convolution while keep performance intact. Meanwhile, an attention mechanism is exploited to recalibrate the fusion modality features adaptively. Refinement components are retained to refine multi-resolution feature maps. We conduct ablative study to demonstrate the availability of our bimodal fusion blocks. Comprehensive experiments validate that the proposed network outperforms the state-of-the-arts and achieves 18 FPS on the challenging RGB-D dataset, NYUDv2. © 2022 IEEE.

关键词： Semantic Segmentation

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A fast algorithm for color image enhancement with total variation regularization

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Science China(Information Sciences) 2010年第9期53卷 1913-1916页

作者： LI Ming1,2 1School of Computer Science and Technology,Huazhong University of Science and Technology,Wuhan 430074,China 2Key laboratory of Education Ministry for image processing and intelligent control,Wuhan 430074,China 1. School of Computer Science and Technology Huazhong University of Science and Technology Wuhan 430074 China2. Key Laboratory of Education Ministry for Image Processing and Intelligent Control Wuhan 430074 China

In this paper,a novel algorithm for color image enhancement is *** proposed method,which is based on Retinex theory and total variational framework,improves the original variational method by using a TV penalty term to force spatial smoothness on the reflectance *** split Bregman algorithm is employed to solve the proposed *** practical experiments,it is verified that our method obtains better enhancement performance and much better calculation efficiency.

关键词： color image enhancement Retinex theory total variational model split Bregman algorithm

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Second-Order Consensus of Multi-agent Systems via Periodically Intermittent Pinning control

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Circuits, Systems, and Signal processing 2016年第7期35卷 2413-2431页

作者： Wang, Xiaoling Su, Housheng Wang, Xiaofan Liu, Bo Department of Automation Shanghai Jiao Tong University and Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai200240 China School of Automation Image Processing and Intelligent Control Key Laboratory of Education Ministry of China Huazhong University of Science and Technology Wuhan430074 China College of Science North China University of Technology Beijing100144 China

In this paper, we investigate the leader-following consensus of second-order multi-agent systems with nonlinear dynamics and time delay by employing periodically intermittent pinning control. All member agents and the virtual leader share the same nonlinear dynamics relating to the velocity and delayed velocity information. Based on Lyapunov stability theory, we obtain a novel criterion that is independent of the time delay and control width to guarantee the second-order consensus of multi-agent systems with time delay and periodically intermittent controllers. Numerical simulations are presented to illustrate the theoretical results. © 2015, Springer Science+Business Media New York.

关键词： Time delay

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image retrieval using the modified intersecting cortical model

Image retrieval using the modified intersecting cortical mod...

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2011 IEEE International conference on intelligent Computation and Bio-Medical Instrumentation, ICBMI 2011

作者： Yuan, Wenjin Zhang, Xuming School of Life Science and Technology Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China Huazhong University of Science and Technology Wuhan China

ISBN: (纸本)9780769546230

The intersecting cortical model(ICM) is driven from the pulse-coupled neural networks (PCNN), and a lot of works have been done on it. In this paper, we have proposed a method, which is modified from the PCNN, to retrieval the image. This method uses the iteration times of the ICM as the feature, and we do it repeatedly. So we will get the feature vectors and utilize the features to retrieval the image. And the experimental results have proved the effectiveness of the proposed method. While the proposed method shows some advantages like the feature curves are linear and steady. © 2011 IEEE.

关键词： image retrieval

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The application of support vector machines and improved particle swarm optimization

The application of support vector machines and improved part...

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2012 International Conference on Modelling, Identification and control, ICMIC 2012

作者： Zhang, Hu Wang, Min Huang, Xinhan Key Laboratory of Image Processing and Intelligent Control of Education Department of Control Science and Engineering Huazhong University of Science and Technology NO.1037 Luoyu Road 430074 Wuhan China

ISBN: (纸本)9780956715715

Parameters selection of support vector machine is the key issue that impacts its accurate performance. A method for support vector regression machine with standard particle swarm optimization (SPSO) algorithm is proposed in this paper. Furthermore, in order to improve the performance of the SPSO algorithm, the concept of the particles' average distance and fitness variance is proposed to make the efficiency of algorithm better. So, the improve algorithm was also applied in this paper. The two different models using SPSO and IPSO respectively were used to forecast the density of the acid-lead battery electrolyte. The experimental results indicate that both SPSO and IPSO have high prediction accuracy and efficiency. The time of the parametric searching by IPSO is obviously decreased to that of SPSO. The mean squared error (MSE) of the prediction model using SPSO is about 2.02056×10-4, Meanwhile, the MSE of the model using IPSO is only about 1.9324×10-4. So, the IPSO algorithm has more superior performance on convergence speed and global optimization. © 2012 Huazhong Univ of Sci & Tec.

关键词： Support vector machines

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A novel estimation strategy for the eye-in-hand depth-independent visual servoing

A novel estimation strategy for the eye-in-hand depth-indepe...

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2011 International Conference on Consumer Electronics, Communications and Networks, CECNet 2011

作者： Liang, Xinwu Huang, Xinhan Wang, Min Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China Dept. of Control Science and Engineering Huazhong University of Science and Technology Wuhan 430074 Hubei China

ISBN: (纸本)9781612844572

As we know, a novel adaptive visual servoing strategy has been proposed for the control of robot manipulators with an eye-in-hand configuration, where an adaptive law is used to estimate the unknown parameters determined by the products of the unknown 3D coordinates and the unknown camera parameters. From a practical point of view, in this paper, we propose a novel strategy for the estimation of these two types of unknown parameters. The new strategy is very useful in that it can reduce the number of the unknown parameters to be estimated. To demonstrate the feasibility of the proposed method, preliminary simulation results based on a two-link planar robot manipulator are presented in this paper. © 2011 IEEE.

关键词： Parameter estimation

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