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A novel ANN-based harmonic extraction method tested with ESN, RNN and MLP in shunt active power filters

International Journal of Wireless and Mobile Computing 2014年第2期7卷 123-131页

作者： Xu, Jinbang Yang, Jun Shen, Anwen Chen, Junfeng Image Processing and Intelligent Control Key Laboratory of Education Ministry of China Department of Control Science and Engineering Huazhong University of Science and Technology Wuhan 430074 China

With the wide use of power conversion devices - 'nonlinear loads' - many harmonic currents are being injected into the power grid. Shunt Active Power Filters (SAPF) are the power electronic equipment to compensate the harmonic currents caused by nonlinear loads. As the foundation of the harmonics recognition and compensation, harmonic extraction is the key technology in SAPF. Artificial Neural Networks (ANN) method has the features of parallel computation and satisfactory results for distorted source voltages over traditional extraction methods. This paper proposes a new harmonic extraction method based on ANN. To test the feasibility of different types of neural networks in this application, this paper compares the performances of three types of ANN: Echo State Networks (ESN), Recurrent Neural Networks (RNN) and Multilayer Perceptron Networks (MLP). © 2014 Inderscience Enterprises Ltd.

关键词： Extraction

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control reconfiguration on deadlocked gimballed thrust of launch vehicle

Lecture Notes in Control and Information Sciences

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Lecture Notes in control and Information Sciences 2014年 452卷 27-59页

作者： Liu, Lei Wang, Yongji Key Laboratory of Ministry of Education for Image Processing and Intelligent Control School of Automation Huazhong University of Science and Technology Wuhan 430074 Hubei China

ISBN: (纸本)9783642363849

An unprecedented challenge of the new generation launch vehicle control is its four parallel strap-on engines are oscillateable by the servomechanism. It increases the manoeuvrability of the vehicle and the control complexity simultaneously. The chapter investigates actuator failure compensation for new generation launch vehicle control. A control reconfiguration scheme of fault-tolerant control is developed to enhance the reliability of launch vehicle attitude control systems and prevent the control invalidation caused by the deadlock of the oscillating actuator, based on the congruity of the composite moment before and after the failure happens. This reconfiguration scheme is capable of utilizing the remaining control authority to achieve the desired performance in the presence of deadlock at certain detectable angle occurring in one or several actuators at unknown time instants. © Springer-Verlag Berlin Heidelberg 2014.

关键词： Launch vehicles

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Multistability analysis of a general class of recurrent neural networks with non-monotonic activation functions and time-varying delays

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Neural networks : the official journal of the International Neural Network Society 2016年 79卷 117-27页

作者： Peng Liu Zhigang Zeng Jun Wang School of Automation Huazhong University of Science and Technology Wuhan 430074 China Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China Wuhan 430074 China. Electronic address: liupengjz@***. Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China Wuhan 430074 China. Electronic address: hustzgzeng@***. Department of Computer Science College of Science and Engineering City University of Hong Kong Kowloon Tong Hong Kong. Electronic address: jwang.cs@cityu.edu.hk.

This paper addresses the multistability for a general class of recurrent neural networks with time-varying delays. Without assuming the linearity or monotonicity of the activation functions, several new sufficient conditions are obtained to ensure the existence of (2K+1)(n) equilibrium points and the exponential stability of (K+1)(n) equilibrium points among them for n-neuron neural networks, where K is a positive integer and determined by the type of activation functions and the parameters of neural network jointly. The obtained results generalize and improve the earlier publications. Furthermore, the attraction basins of these exponentially stable equilibrium points are estimated. It is revealed that the attraction basins of these exponentially stable equilibrium points can be larger than their originally partitioned subsets. Finally, three illustrative numerical examples show the effectiveness of theoretical results.

关键词： Cohen–Grossberg neural networks Multistability Non-monotonic activation functions Time-varying delays

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A research on human cognitive modeling in rumor spreading based on HTM

Communications in Computer and Information Science

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Communications in Computer and Information Science 2014年 461卷 268-277页

作者： Li, Xiangchen Chen, X. Wang, Wei School of Automation Huazhong University of Science and Technology Wuhan China Image Processing and Intelligent Control Key Laboratory of Education Ministry of China Wuhan China

ISBN: (纸本)9783662452820

As a sociological phenomenon, rumor spreading has been widely researched by sociologists and other fields’ scholars. How do people generate those strange thinking about the rumor? This paper, from artificial intelligence view, focuses on an algorithm based on Hierarchical Temporal Memory (HTM) to simulate human cognitive process of generating rumors from individual heterogeneous living experience. Comparison with classical Bayesian Networks, our algorithm could effectively and really simulate human cognitive process of rumors, and in accordance with some typical psychology effects proved by sociologists and psychologists. © Springer-Verlag Berlin Heidelberg 2014.

关键词： Bayesian networks

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A new automatic mass detection method for breast cancer with false positive reduction

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Neurocomputing 2015年 152卷 388-402页

作者： Xiaoming Liu Zhigang Zeng School of Automation Huazhong University of Science and Technology Wuhan 430074 China Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China Wuhan 430074 China College of Computer Science and Technology Wuhan University of Science and Technology Wuhan 430081 China Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System Wuhan 430081 China

Mass localization is a crucial problem in computer-aided detection (CAD) system for the diagnosis of suspicious regions in mammograms. In this paper, a new automatic mass detection method for breast cancer in mammographic images is proposed. Firstly, suspicious regions are located with an adaptive region growing method, named multiple concentric layers (MCL) approach. Prior knowledge is utilized by tuning parameters with training data set during the MCL step. Then, the initial regions are further refined with narrow band based active contour (NBAC), which can improve the segmentation accuracy of masses. Texture features and geometry features are extracted from the regions of interest (ROI) containing the segmented suspicious regions and the boundaries of the segmentation. The texture features are computed from gray level co-occurrence matrix (GLCM) and completed local binary pattern (CLBP). Finally, the ROIs are classified by means of support vector machine (SVM), with supervision provided by the radiologist׳s diagnosis. To deal with the imbalance problem regarding the number of non-masses and masses, supersampling and downsampling are incorporated. The method was evaluated on a dataset with 429 craniocaudal (CC) view images, containing 504 masses. Among them, 219 images containing 260 masses are used to optimize the parameters during MCL step, and are used to train SVM. The remaining 210 images (with 244 masses) are used to test the performance. Masses are detected with 82.4% sensitivity with 5.3 false positives per image (FPsI) with MCL, and after active contour refinement, feature analysis and classification, it obtained 1.48 FPsI at the sensitivity 78.2%. Testing on 164 normal mammographic images showed 5.18 FPsI with MCL and 1.51 FPsI after classification. Experiments on mediolateral oblique (MLO) images have also been performed, the proposed method achieved a sensitivity 75.6% at 1.38 FPsI. The method is also analyzed with free response operating characteristi

关键词： Mass detection Breast cancer Level set Local binary pattern Support vector machine

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Tissue P Systems with Look-ahead Mode

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Chinese Journal of Electronics 2014年第1期23卷 81-86页

作者： JIANG Yun SONG Tao ZHANG Zheng School of Computer Science and Information Engineering Chongqing Technology and Business University Image Processing and Intelligent Control Key Laboratory of Education Ministry of China Department of Control Science and Engineering Huazhong University of Science and Technology

Tissue P systems are a class of distributed and parallel computing models inspired from inter-cellular communication and cooperation between cells. In this work, a variant of tissue P system, named tissue P system with look-ahead mode, is discussed for decreasing the inherent non-determinism of tissue P systems and helping implementing tissue P systems on computers. Such systems are proved to be universal by simulating register machine, and they are also proved to be able to efficiently solve computationally hard problems by means of a spacetime tradeoff, which is illustrated with a polynomial solution to 3-coloring problem.

关键词： Tissue P system Look-ahead mode Recursively enumerable language Cell separation 3-Coloring

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Self-triggered Based Semi-global Consensus Tracking of Multi-agent Systems with Input Saturation

Self-triggered Based Semi-global Consensus Tracking of Multi...

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第三十四届中国控制会议

作者： Xiaoling Wang Housheng Su Jiwei Li Xiaofan Wang Department of Automation Shanghai Jiaotong University and Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai 200240 P. R. China School of Automation Image Processing and Intelligent Control Key Laboratory of Education Ministry of China Huazhong University of Science and Technology Luoyu Road 1037 Wuhan 430074 P. R. China

ISBN: (纸本)9781467374439

Self-triggered control is a technique which can determine the next sampling instant by virtue of the last sampling information. Combining this technique and the low-gain feedback one, we investigate the consensus tracking of general linear multi-agent systems with input saturation and updating delays in this paper. Specific formulations of heterogenous updating delays and heterogenous sampling periods are acquired to guarantee the semi-global consensus tracking of multi-agent systems. Numerical simulations are provided to verify the main results.

关键词： Multi-agent Systems Consensus Tracking Self-triggered Technique Input Saturation Low-gain Feedback Multi-agent systems sampling time tracking

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Cell resistance slope combined with LVQ neural network for prediction of anode effect

Cell resistance slope combined with LVQ neural network for p...

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International Conference on intelligent control and Information processing (ICICIP)

作者： Kaibo Zhou Zhikai Lin Dengzhi Yu Bin Cao Ziqian Wang Sihai Guo School of Automation Key Laboratory of Ministry of Education for Image Processing and Intelligent Control Wuhan China Guiyang Aluminum Magnesium Design and Research Institute Guiyang China School of Automation Wuhan University of Technology Wuhan China

It is an important part in aluminum electrolysis production to control the anode effect (AE). Since there are some shortcomings in traditional methods of anode effect prediction in aluminum electrolysis, this paper combined two methods, the slope of cell resistance and learning vector quantization (LVQ) neural network, to predict anode effect. First of all, the first prediction of anode effect will be conducted based on the slope of cell resistance. Afterwards, the inaccurate data are supposed to be re-predicted. The second prediction consists of two steps, one is to estimate the power spectrum from the signal of cell resistance by means of periodogram, the other is to re-predict the anode effect with the LVQ neural network, since the energy of frequency bands are served as the input feature variables of neural network, so as to raise the accuracy of prediction. It turned out that the success rate of ten-minute in advance prediction for anode effect can be above 85%, though just cell resistance signal is studied.

关键词： Resistance Decision support systems Neural networks Spectral analysis Data acquisition Vector quantization

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Global coordinated tracking of multi-agent systems with disturbance uncertainties via bounded control inputs

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Nonlinear Dynamics 2015年第4期82卷 2059-2068页

作者： Su, Housheng Chen, Michael Z. Q. Wang, Xiaofan School of Automation Image Processing and Intelligent Control Key Laboratory of Education Ministry of China Huazhong University of Science and Technology Wuhan China Department of Mechanical Engineering The University of Hong Kong Pokfulam Hong Kong Department of Automation Shanghai Jiao Tong University Shanghai China

This paper investigates the problem of global coordinated tracking of a multi-agent system with input additive uncertainties and disturbances via bounded control inputs. Scheduled low-and-high gain feedback-based distributed coordinated tracking protocols are developed. It is shown that, under the assumptions that each agent is asymptotically null controllable with bounded controls and the network is connected, global coordinated tracking of the multi-agent system can be achieved. We finally show some numerical simulations to verify and illustrate the theoretical results.

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Discovering distinctive action parts for action recognition

Discovering distinctive action parts for action recognition

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作者： Chen, Feifei Sang, Nong Gao, Changxin Kuang, Xiaoqin Key Laboratory of Ministry of Education for Image Processing and Intelligent Control School of Automation Huazhong University of Science and Technology China

ISBN: (纸本)9781479957514

Recent methods based on mid-level visual concepts have shown promising capability in human action recognition field. Automatically discovering semantic entities such as parts for an action class remains challenging. In this paper, we focus on discovering distinctive action parts for recognition of human actions by learning and selecting a small number of discriminative part detectors directly from training videos. We initially train a large collection of candidate Exemplar-LDA detectors from clusters obtained by clustering spatiotemporal patches in whitened space. A novel Coverage-Entropy curve is proposed as a means of measuring the representative and discriminative capabilities of part detectors, and used to select a set of compact and meaningful detectors out of the vast candidates. By integrating these mined detectors into 'bag of parts' representation, our approach demonstrates state-of-the-art performance on the UCF50 dataset. © 2014 IEEE.

关键词： Semantics

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