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检索条件"机构=Hubei Key Laboratory of Advance Control and Intelligent Automation for Complex"

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Analysis and circuit implementation of a new fourth-order multi-wing chaotic system based on memristors

Analysis and circuit implementation of a new fourth-order mu...

引用

Chinese automation Congress (CAC)

作者： Lei Jia Xiaowei Jiang Xianhe Zhang Ming Chi Hubei Key Laboratory of Advanced Control and Intelligent Automation of Complex Systems Engineering Research Center of Intelligent Geodetection Technology Ministry of Education School of Automation China University of Geosciences Wuhan P. R. China School of Electrical Engineering and Automation Hubei Normal University Huangshi P. R. China School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan P. R. China

ISBN: (纸本)9781665426480

In this paper, a new fourth-orders memristor chaotic system is obtained by introducing a smooth memristor model as the feedback term based on the modified three-orders chaotic system. The system can generate double-wing, four-wing chaos or hyperchaos for different parameters and initial conditions. Through the analysis of Lyapunov exponent and other dynamics, we can see that the system has complex chaotic, hyperchaotic, and continuous chaotic. Other dynamical behaviors such as multi-stability and extreme multi-stability are found by comparing phase and bifurcation diagrams, and equilibrium point calculations. Finally, the chaotic behavior is successfully verified by circuit simulation.

关键词： Chaos automation Circuit simulation Buildings Memristors Bifurcation Encryption

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A Reinforcement-Learning-Based Evolutionary Algorithm Using Solution Space Clustering For Multimodal Optimization Problems

A Reinforcement-Learning-Based Evolutionary Algorithm Using ...

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Congress on Evolutionary Computation

作者： Hai Xia Changhe Li Sanyou Zeng Qingshan Tan Junchen Wang Shengxiang Yang School of Automation China University of Geosciences Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems School of Mechanical Engineering and Electronic Information China University of Geosciences Wuhan China School of Computer Science and Informatics De Montfort University Leicester United Kingdom

In evolutionary algorithms, how to effectively select interactive solutions for generating offspring is a challenging problem. Though many operators are proposed, most of them select interactive solutions (parents) randomly, having no specificity for the features of landscapes in various problems. To address this issue, this paper proposes a reinforcement-learning-based evolutionary algorithm to select solutions within the approximated basin of attraction. In the algorithm, the solution space is partitioned by the k-dimensional tree, and features of subspaces are approximated with respect to two aspects: objective values and uncertainties. Accordingly, two reinforcement learning (RL) systems are constructed to determine where to search: the objective-based RL exploits basins of attraction (clustered subspaces) and the uncertainty-based RL explores subspaces that have been searched comparatively less. Experiments are conducted on widely used benchmark functions, demonstrating that the algorithm outperforms three other popular multimodal optimization algorithms.

关键词： Uncertainty Clustering algorithms Evolutionary computation Reinforcement learning Benchmark testing Search problems Feature extraction

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A Novel Scalable Framework For Constructing Dynamic Multi-objective Optimization Problems

A Novel Scalable Framework For Constructing Dynamic Multi-ob...

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Congress on Evolutionary Computation

作者： Qingshan Tan Changhe Li Hai Xia Sanyou Zeng Shengxiang Yang School of Automation China University of Geosciences Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems School of Mechanical Engineering and Electronic Information China University of Geosciences Wuhan China School of Computer Science and Informatics De Montfort University Leicester United Kingdom

Modeling dynamic multi-objective optimization problems (DMOPs) has been one of the most challenging tasks in the field of dynamic evolutionary optimization. Based on the analysis of the existing DMOPs, several features widely existed in real-world applications are not taken into account: different objectives may have different function models and variables to be optimized; and the number of conflicting variables should be independent from the number of objectives; the time-linkage property is not considered. In order to overcome the above issues, a novel framework for constructing DMOPs is proposed, where all objectives can be designed independently, and the number of the conflicting variables can be tuned by users. Moreover, it is easy to add new dynamic features to this framework. Several classical dynamic multi-objective optimization algorithms are tested on four scenarios, results show that these characteristics are challenging for the existing algorithms.

关键词： Schedules Analytical models Heuristic algorithms Object oriented modeling Evolutionary computation Benchmark testing Dynamic scheduling

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Adaptive control for asynchronously switched fractional-order multi-agent systems

Adaptive control for asynchronously switched fractional-orde...

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第三十九届中国控制会议

作者： Xiongliang Zhang Shiqi Zheng Feng Liu Mingyuan Zhao Yuan Sun School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation of Complex Systems School of Electrical and Electronic Engineering The University of Adelaide

In this paper, we discuss the adaptive controller design for a class of fractional-order（FO） multi-agent systems（MAS）.All the agents are described by FO pure-feedback nonlinear systems. This is more general than the existing works, which only considered strict-feedback or integer-order nonlinear systems. Meanwhile, asynchronous switching are considered in FO MAS,meaning the agents have heterogeneous switching dynamics. A new neural network based adaptive controller is proposed for the considered FO MAS, which can make the consensus tracking error converge to a small neighborhood of origin. Simulation verifies the results obtained.

关键词： Consensus tracking fractional-order multi-agent systems asynchronously switched systems

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KSLIC: K-mediods clustering based simple linear iterative clustering 1

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

作者： Zhang, Houwang Zhu, Yuan School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China

ISBN: (数字)9783030317232

ISBN: (纸本)9783030317225

Simple Linear Iterative Clustering (SLIC) is one of the most excellent superpixel segmentation algorithms with the most comprehensive performance and is widely used in various scenes of production and living. As a preprocessing step in image processing, superpixel segmentation should meet various demands in real life as much as possible, but SLIC is highly sensitive to noise. In this paper, a K-mediods clustering based simple linear iterative clustering (KSLIC) is proposed, which replaces the K-means clustering in SLIC with a modified local K-mediods clustering. To evaluate the performance of KSLIC, we test it on BSD500 benchmark dataset. The results show that it outperforms SLIC in terms of different noise environments including Gaussian noise, multiplicative noise and salt and pepper noise. © Springer Nature Switzerland AG 2019.

关键词： Salt and pepper noise

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H∞ Consensus control for Discrete-Time Stochastic Multi-agent Systems with Infinite Markov Jumps

H∞ Consensus Control for Discrete-Time Stochastic Multi-age...

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Annual Conference of Industrial Electronics Society

作者： Jie Wang Xin Chen School of Automation China University of Geosciences Wuhan P. R. China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

ISBN: (数字)9781728154145

ISBN: (纸本)9781728154152

This paper focuses on multi-agent systems under the disturbances of parameter uncertainties, noises and external disturbances simultaneously, which are more suitable for the changing environments than most ideal models. For this case, the robust H∞ consensus control problem is studied to attenuate the influence of disturbances below a given level. We aim to design a consensus controller such that the closed-loop muti-agent systems reach the desired H ∞ performance. By tools of Kronecker product, graph theory, and infinite horizon bounded real lemma, sufficient conditions for existence of H ∞ consensus protocol design are obtained in terms of linear matrix inequalities (LMIs). Finally, a numerical example is given to show the validity of the method.

关键词： Multi-agent systems Symmetric matrices Markov processes Stochastic systems Robot sensing systems Eigenvalues and eigenfunctions Topology

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A threshold segmentation method for non-uniform illumination image based on brightness equalization 2

A threshold segmentation method for non-uniform illumination...

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2019 2nd International Conference on advanced Materials, intelligent Manufacturing and automation, AMIMA 2019

作者： Guo, Hui Chen, Peng Huang, Shun Hu, Cong Zhang, Lijun School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex System Wuhan430074 China

In the process of image acquisition, non-uniform illumination images are common due to poor lighting, surface reflection, or a combination of these two factors. In order to improve the quality of image segmentation, an image threshold segmentation method is proposed for non-uniform illumination images. First, the brightness of different regions in the image is compensated to make the brightness background of the whole image consistent. Second, the gradation histogram of the processed image is obtained and simulated into Gaussian distribution curve, then the inflection points of the curve are calculated. Finally, the two inflection points are set as thresholds to segment the image after brightness equalization. This method eliminates the influence of non-uniform illumination to a certain extent and gets a better segmentation effect. Experiments were carried out on images containing several different types of non-uniform illumination. The results demonstrate that the proposed method outperforms the compared enhancement algorithms in threshold segmentation. © Published under licence by IOP Publishing Ltd.

关键词： Luminance

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Image retrieval based on convolutional neural network and linear discriminate analysis 2

Image retrieval based on convolutional neural network and li...

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2019 2nd International Conference on advanced Materials, intelligent Manufacturing and automation, AMIMA 2019

作者： Xia, Wei Hu, Cong Cheng, Xianghui Chen, Peng Jin, Xing School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex System Wuhan430074 China

Image retrieval is a hot research topic in the field of computer vision image processing, and the user queries the image database for similar images and produces a list of recommendations. The paper firstly sets forth the research status of image retrieval, then the convolution neural network is briefly introduced. Due to the traditional image retrieval and recommendation system use manual extraction of image features is relatively cumbersome, and the retrieval accuracy is not high research status, the paper proposes an image retrieval method based on the improved convolutional neural network and linear discriminate analysis. Caltech256 and CIFAR-10 datasets were trained using the model in this paper, experimental, results show that the proposed method can effectively improve the performance of retrieval. © Published under licence by IOP Publishing Ltd.

关键词： Search engines

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Chinese Calligraphy Character Generating via CGAN with a Multi-subnet Parallel and Cascade Generator

Chinese Calligraphy Character Generating via CGAN with a Mul...

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第三十九届中国控制会议

作者： Xiaoxue Zhou Ziying Zhang Xin Chen Mengxi Qin School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems School of Arts and Communication China University of Geosciences

Chinese character generation is one of the key technologies in Chinese character intelligent design. Most generation methods cannot solve the situation where the generated Chinese character strokes have artifact or even miss. The main reason is that the generator is not strong enough. Therefore, in this paper, we propose a multi-subnet parallel and cascade generator, which combines the conditional generation adversarial network（CGAN） to realize the generation of calligraphy Chinese *** method divides a Chinese character generation task into several parts undertaken by each sub-generator, and the output of each sub-generator will contain certain image information, which will increase with the rise of sub-generator hierarchy. It allows each sub-generator to focus on its own task, generating more realistic characters eventually. Finally, the test set performs better than the CGAN with a single generator.

关键词： CGAN Chinese calligraphy character generation Multi-subnet parallel and cascade generator

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Drone Image Stitching Using Local Least Square Alignment

Drone Image Stitching Using Local Least Square Alignment

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IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Qi Wan Linbo Luo Jun Chen Yong Wang Donghai Guo School of Mechanical Engineering and Electronic Information China University of Geosciences Wuhan Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

ISBN: (数字)9781728163741

ISBN: (纸本)9781728163758

This paper proposes a strategy for drone image stitching using local least square alignment, which aims to effectively stitch multiple overlapping drone images into a natural panoramic image. Existing traditional methods using simple homography cannot handle the situation that the input drone images have parallax effect, and the mosaic result always suffers from artifacts. In order to achieve natural-looking stitching results without the above limitation, we divide the proposed method into the following two steps, namely, local least square alignment and global similarity constraint. Starting from initial feature sets obtained by traditional feature extraction methods, we construct a robust alignment energy based on parallax errors to adaptively eliminate parallax effects. The energy can be efficiently minimized used least square estimate. Combined with global similarity constraint, our proposed strategy can flexibly improve the naturalness of the results. Experiments show that our stitching strategy can more effectively eliminate parallax effects and achieve natural-looking results compared to other state-of-the-art methods.

关键词： Drones Image stitching Distortion Feature extraction Optimization Geology Adaptation models

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