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The 33th Chinese control Conference第33届中国控制会议

作者： Xiaofan Wang Xiaoling Wang Housheng Su Department of Automation Shanghai Jiaotong Universityand Key Laboratory of System Control and Infor School of Automation Image Processing and Intelligent Control Key Laboratory of Education Ministry o

ISBN: (纸本)9781479947249

Consensus in multi-agent systems means that reach an agreement among states of the whole ***,almost all the existed works on consensus have been in the description of the states of nodes,and fewer efforts have been devoted to the consensus taking place on the edges of multi-agent *** this paper,we focus on the dynamics proceed on the edges and establish a discrete-time and a continuous-time edge consensus protocols respectively for directed multi-agent *** mapping the edge topology to its line graph of the original nodal topology,we analyze the consensus of the edge protocols rigorously,and get that both the discrete-time protocol and the continuous-time protocol of directed multi-agent systems can guarantee that an edge consensus is asymptotically reached for all initial states when the original directed system is strongly *** simulations are provided to show the effectiveness of both the discrete-time and the continuous-time models.

关键词： Consensus Edge Protocol Multi-agent Systems Line Graph

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Implementation of Memristive Neural Networks with Spike-rate-dependent Plasticity Synapses

Implementation of Memristive Neural Networks with Spike-rate...

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International Joint Conference on Neural Networks

作者： Yide Zhang Zhigang Zeng Shiping Wen School of Automation Huazhong University of Science and Technology and Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China

ISBN: (纸本)9781479914821

The property of changing resistance according to applied currents of memristors makes them candidates for emulating synapses in artificial neural networks. In this paper, we introduce a memristive synapse design into neural network circuits. Combined with modified integrate-and-fire (I&F) complementary metal-oxide-semiconducter (CMOS) neurons, the memristive neural network shows similarities to its biological counterpart, in respect of biologically realistic, current-controlled spikes and adaptive synaptic plasticity. Then, the spike-rate-dependent plasticity (SRDP) of the synapse, an extended protocol of the Hebbian learning rule, is originally implemented by the circuit. And some advanced neural activities including learning, associative memory and forgetting are realized based on the SRDP rule. These activities are comprehensively validated on a neural network circuit inspired by famous Pavlov's dog-experiment with simulations and quantitative analyses.

关键词： Neurons Memristors Biological neural networks Biological system modeling Protocols Semiconductor device modeling Integrated circuit modeling

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Genetic Algorithm based Neural Network for the Displacement of Landslide Forecasting

Genetic Algorithm based Neural Network for the Displacement ...

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第三十三届中国控制会议

作者： Jiejie Chen Zhigang Zeng Ping Jiang Huiming Tang The School of Automation Huazhong University of Science and Technology Key Laboratory of Image Information Processing and Intelligent Control Ministry Education Faculty of Engineering China University of Geosciences

This paper proposes two hybrid prediction models using for predicting the displacement of landslide, Genetic Algorithm-Radial Basis Function Neural Network (GA-RBFN) and Genetic Algorithm- Back Propagation Neural Network (GA-BPNN). A case study of Yuhuangge landslide in the Three Gorges reservoir in China is used to illustrate the capability and merit of our schemes. In addition, the result shows that GP-BPNN get better accuracy than GA-RBFN in the same measurements.

关键词： Terrain factors Genetic algorithms Neural networks Forecasting Training Transfer functions Educational institutions

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A cooperative immune coevolutionary algorithm for multi-objective optimization

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Tien Tzu Hsueh Pao/Acta Electronica Sinica 2014年第5期42卷 858-867页

作者： Qi, Yu-Tao Liu, Fang Ren, Yuan Liu, Jing-Le Jiao, Li-Cheng School of Computer Science and Technology Xidian University Xi'an Shaanxi 710071 China Institute of Intelligent Information Processing Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education Xidian University Xi'an Shaanxi 710071 China

According to the distribution characteristics of the Pareto set (PS) of multi-objective optimization problems (MOPs), a cooperative coevolutionary model with new problem decomposition method was designed. By introducing the proposed coevolutionary model into artificial immune system, a cooperative immune coevolutionary algorithm for multi-objective optimization (CICAMO) was proposed. In CICAMO, the Tchebycheff decomposition method is employed to divide sub-populations at first, and then linear probabilistic models are built for each sub-population to piecewise approximate the distribution of the whole PS. In antibody reproducing step, two types of approaches based on clonal selection and model sampling are employed. Experimental results indicate that CICAMO can achieve a good performance in terms of both solution quality and convergence rate, especially when solving MOPs with non-linear relationship between decision variables.

关键词： Multiobjective optimization

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Partition Region-based Fuzzy Contour Model for Auroral Oval Segmentation

Partition Region-based Fuzzy Contour Model for Auroral Oval ...

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2014中国极地科学学术年会

作者： Jiao Shi Jiaji Wu Xidian University Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education Institute of Intelligent Information Processing Xi''an Shaanxi 710071China

The aurora is a natural light phenomenon in the sky, particularly in high-latitude *** is caused by the collision of energetic charged particles from the earth's magnetosphere and solar *** aurora is not only an optical *** also emits radio waves and has a strong influence on radio communications, on the weather, and on complex biological *** study of auroral activity attracts great interest form geophysicists due to its utility in analyzing high-latitude ionosphere-thermosphere-magnetosphere behaviors.A major source of images available for studying auroral activity consists of data collected by the Polar Ultraviolet imager (UVI).

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Nonlinear H ∞ observer design for one-sided Lipschitz systems

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Neurocomputing 2014年 145卷 505-511页

作者： Wei Zhang Housheng Su Shengchao Su Dazhong Wang Laboratory of Intelligent Control and Robotics Shanghai University of Engineering Science Shanghai 201620 China School of Automation Image Processing and Intelligent Control Key Laboratory of Education Ministry of China Huazhong University of Science and Technology Wuhan 430074 China College of Information Science and Technology Donghua University Shanghai 201620 China

This paper is considered with the H ∞ observer design problem for a class of nonlinear systems with the one-sided Lipschitz condition. The systems under consideration include the well-studied Lipschitz system as a special case and possess inherent advantages with respect to conservativeness. For such systems in the presence of noises, we develop a Linear Matrix Inequality (LMI) based approach to design a nonlinear H ∞ observer by carefully dealing with the one-sided Lipschitz condition together with the quadratic inner-bounded condition. The resulting nonlinear H ∞ observer guarantees asymptotic stability of the estimation error dynamics with a prescribed H ∞ performance. Moreover, for the design purpose, the existence condition of the proposed nonlinear H ∞ observer is formulated in terms of LMIs by using a matrix generalized inverse technique. Finally, a simulation example is given to illustrate the effectiveness of the proposed design.

关键词： One-sided Lipschitz nonlinear systems Nonlinear H ∞ observers Observer design State estimation

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Vessel segmentation in retinal images with a multiple kernel learning based method

Vessel segmentation in retinal images with a multiple kernel...

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International Joint Conference on Neural Networks (IJCNN)

作者： Xiaoming Liu Zhigang Zeng Xiaoping Wang College of Computer Science and Technology Wuhan University of Science and Technology Wuhan China Key Laboratory of Image Information Processing and Intelligent Control Ministry of Education Wuhan China

Blood vessel segmentation is an important problem for quantitative structure analysis of retinal images, and many diseases are related to the structure changes. Manual segmentation is time consuming and computer aided segmentation is required to deal with large amount images. This paper presents a new supervised method for segmentation of blood vessels in retinal photographs. Multiple kernel learning (MKL) is introduced to deal with the problem, utilizing features from Hessian matrix based vesselness measure, response of multiscale Gabor filter, and multiple scale line strength features. The method is evaluated on the publicly available DRIVE and STARE databases. The performance of the MKL method is evaluated and experimental results show the high accuracy of the proposed method.

关键词： image segmentation Retina Biomedical imaging Kernel Blood vessels Accuracy Support vector machines

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Semi-supervised Fisher-Markov Selector via Manifold Regularization

Semi-supervised Fisher-Markov Selector via Manifold Regulari...

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2012 International Conference on Applied Informatics and Communication(ICAIC 2012)

作者： Dong Chen Lin Zhu JieYang Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University and Key Laboratory of System Control and Information Processing Ministry of Education of China

Feature subset selection is an important approach to deal with high-dimensional data. But selecting the best subset of data is NP hard. So most of feature selection methods cannot handle high-dimensional data efficiently, or they can only obtain local optimum instead of global optimum. In these cases, when the data consist of both labeled and unlabeled data, semi-supervised feature selection can make full use of data information. In this paper, we introduce a novel semi-supervised feature selection algorithm, which is a filter method based on Fisher-Markov selector, thus ours can achieve global optimum and computational efficiency under certain kernels.

关键词： Feature selection, Dimensionality reduction, Manifold regularization, Semi-supervised learning

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Exponential synchronization of coupled memristive neural networks via pinning control

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Chinese Physics B 2013年第5期22卷 203-212页

作者：王冠沈轶尹泉 Department of Control Science and Engineering Huazhong University of Science and Technology Key Laboratory of Ministry of Education for Image Processing and Intelligent Control

This paper is concerned with the exponential synchronization problem of coupled memristive neural networks. In contrast to general neural networks, memristive neural networks exhibit state-dependent switching behaviors due to the physical properties of memristors. Under a mild topology condition, it is proved that a small fraction of controlled sub- systems can efficiently synchronize the coupled systems. The pinned subsystems are identified via a search algorithm. Moreover, the information exchange network needs not to be undirected or strongly connected. Finally, two numerical simulations are performed to verify the usefulness and effectiveness of our results.

关键词： synchronization memristor coupled neural networks pinning control

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Adaptive synchronization of complex dynamical networks with time-varying delays

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Circuits, Systems, and Signal processing 2014年第4期33卷 1173-1188页

作者： Liu, Bo Wang, Xiaoling Su, Housheng Zhou, Hongtao Shi, Yuntao Li, Rong College of Science North China University of Technology Beijing 100144 China Department of Automation Shanghai Jiao Tong University Ministry of Education of China Shanghai 200240 China School of Automation Key Laboratory of Education Ministry for Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan 430074 China Key Laboratory of Beijing for Field-bus Technology and Automation North China University of Technology Beijing 100144 China Department of Applied Mathematical Sciences Shanghai Finance University Shanghai 201209 China

This paper addresses the problem of adaptive pinning synchronization of complex dynamical networks with nonlinear delayed intrinsic dynamics and time-varying delays. By introducing decentralized adaptive strategies to both the coupling strengths and the feedback gains, it is proved that the complex dynamical network can synchronize with the desired state for the bounded time-varying delays even when only one node is informed, without any global information of the underlying network. Finally, some numerical simulations are given to verify the main results and show the superiority of these self-designed adaptive strategies. © 2013 Springer Science+Business Media New York.

关键词： Complex networks

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