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arXiv 2017年

作者： Huang, Xiaolin Yan, Ming Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University MOE Key Laboratory of System Control and Information Processing Shanghai200240 China Department of Computational Mathematics Science and Engineering Department of Mathematics Michigan State University East LansingMI48824 United States

One-bit measurements widely exist in the real world and can be used to recover sparse signals. This task is known as one-bit compressive sensing (1bit-CS). In this paper, we propose novel algorithms based on both convex and nonconvex sparsity-inducing penalties for robust 1bit-CS. We consider the dual problem, which has only one variable and provides a sufficient condition to verify whether a solution is globally optimal or not. For positive homogeneous penalties, a globally optimal solution can be obtained in two steps: a proximal operator and a normalization step. For other penalties, we solve the dual problem, and it needs to evaluate the proximal operators for many times. Then we provide fast algorithms for finding analytical solutions for three penalties: minimax concave penalty (MCP), 0norm, and sorted 1penalty. Specifically, our algorithm is more than 200 times faster than the existing algorithm for MCP. Its efficiency is comparable to the algorithm for the 1penalty in time, while its performance is much better than 1. Among these penalties, sorted 1is most robust to noise in different settings. Copyright © 2017, The Authors. All rights reserved.

关键词： Compressed sensing

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Association rule analysis for tour route recommendation and application to WCTSNOP

Association rule analysis for tour route recommendation and ...

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ISPRS Geospatial Week 2017

作者： Fang, Hui Chen, Chongcheng Lin, Jiaxiang Liu, Xianfeng Fang, Dong Laboratory of Spatial Data Mining and Information Sharing of Ministry of Education Spatial Information Research Centre of Fujian Fuzhou University District Xueyuan Road China Dept. of Computer Science Fujian Provincial Key Laboratory of Information Processing and Intelligent Control Minjiang University Fuzhou University District Xiyuangong Road China College of Computer and Information Sciences Fujian Agriculture and Forestry University Fuzhou China Fuzhou Silviscene Information Technology Co. Ltd. China

The increasing E-tourism systems provide intelligent tour recommendation for tourists. In this sense, recommender system can make personalized suggestions and provide satisfied information associated with their tour cycle. Data mining is a proper tool that extracting potential information from large database for making strategic decisions. In the study, association rule analysis based on FP-growth algorithm is applied to find the association relationship among scenic spots in different cities as tour route recommendation. In order to figure out valuable rules, Kulczynski interestingness measure is adopted and imbalance ratio is computed. The proposed scheme was evaluated on Wangluzhe cultural tourism service network operation platform (WCTSNOP), where it could verify that it is able to quick recommend tour route and to rapidly enhance the recommendation quality. © Authors 2017. CC BY 4.0 License.

关键词： Data mining

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Robust Monocular Visual Odometry using Optical Flows for Mobile Robots 35

Robust Monocular Visual Odometry using Optical Flows for Mob...

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第35届中国控制会议

作者： LI Haifeng HU Zunhe CHEN Xinwei College of Computer Science and Technology Civil Aviation University of China Fujian Provincial Key Laboratory of Information Processing and Intelligent Control Department of Computer Science Minjiang University

ISBN: (纸本)9781509009107

A robust optical flow-based visual odometry method using a single onboard camera is proposed in this *** improve the quality of the noisy optical flows,a correction method across multiple frames is ***,the optical flows in the plane at infinity are detected and removed as these optical flows have very low signal to noise ratio for robot translation ***,a RANSAC approach for robot ego-motion estimation is *** experiments are carried out and the results show that the proposed method is able to estimate the camera trajectory robustly with reasonable accuracy.

关键词： visual odometry optical flows mobile robot

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controllability of giant connected components in a directed network

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Physical Review E 2017年第4期95卷 042318-042318页

作者： Xueming Liu Linqiang Pan H. Eugene Stanley Jianxi Gao Key Laboratory of Image Information Processing and Intelligent Control of Education Ministry of China School of Automation Huazhong University of Science and Technology Wuhan 430074 Hubei China Center for Polymer Studies and Department of Physics Boston University Boston Massachusetts 02215 USA School of Electric and Information Engineering Zhengzhou University of Light Industry Zhengzhou 450002 Henan China Center for Complex Network Research and Department of Physics Northeastern University Boston Massachusetts 02115 USA

When controlling a complex networked system it is not feasible to control the full network because many networks, including biological, technological, and social systems, are massive in size and complexity. But neither is it necessary to control the full network. In complex networks, the giant connected components provide the essential information about the entire system. How to control these giant connected components of a network remains an open question. We derive the mathematical expression of the degree distributions for four types of giant connected components and develop an analytic tool for studying the controllability of these giant connected components. We find that for both Erdős-Rényi (ER) networks and scale-free (SF) networks with p fraction of remaining nodes, the minimum driver node density to control the giant component first increases and then decreases as p increases from zero to one, showing a peak at a critical point p=pm. We find that, for ER networks, the peak value of the driver node density remains the same regardless of its average degree 〈k〉 and that it is determined by pm〈k〉. In addition, we find that for SF networks the minimum driver node densities needed to control the giant components of networks decrease as the degree distribution exponents increase. Comparing the controllability of the giant components of ER networks and SF networks, we find that when the fraction of remaining nodes p is low, the giant in-connected, out-connected, and strong-connected components in ER networks have lower controllability than those in SF networks.

关键词： Network structure

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Fuzzy control for Uncertain Vehicle Active Suspension Systems via Dynamic Sliding-Mode Approach

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IEEE Transactions on Systems, Man, and Cybernetics: Systems 2017年第1期47卷 24-32页

作者： Wen, Shiping Chen, Michael Z. Q. Zeng, Zhigang Yu, Xinghuo Huang, Tingwen School of Automation Huazhong University of Science and Technology Wuhan430074 China Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China Wuhan430074 China Department of Mechanical Engineering University of Hong Kong Hong Kong Hong Kong Platform Technologies Research Institute RMIT University MelbourneVIC3001 Australia Texas A and M University at Qatar Doha23874 Qatar

This paper investigates the fuzzy control issue for uncertain active suspension systems via dynamic sliding-mode method. The Takagi-Sugeno fuzzy approach is adopted on the background of the varying masses to describe the prescribed nonlinear system in order to achieve the design targets via the method of sector nonlinearity. This paper employs the dynamic sliding-mode scheme to control nonlinear active suspension systems. In the proposed sliding-mode control scheme, the sliding surface function is formed linearly with the system states and control inputs. Then, a fuzzy dynamic term is utilized to construct the sliding-mode feedback controller. In existing results, the sliding mode is achieved and maintained with no consideration of the system perturbations. Thus, sufficient conditions are proposed to make the sliding surface reachable with the existence of the system perturbations to make the augmented system stable. Finally, simulation results are presented to verify the effectiveness of the proposed schemes. © 2013 IEEE.

关键词： Robust control

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Transitioning conditional probability to discriminative classifier over inductive reasoning

Transitioning conditional probability to discriminative clas...

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International Conference on Awareness Science and Technology (iCAST)

作者： Peng Mei Fuquan Zhang Lin Xu Hongyong Leng Lei Chen Guo Liu School of Software Beijing Institute of Technology Beijing China Fujian Provincial Key Laboratory of Information Processing and Intelligent Control Minjiang University Fuzhou China Innovative Information Industry Research Institute Fujian Normal University Fuzhou China

Overcome context-independent probabilities based reasoning, with decomposition of categories and predicates into features as non-stable predicates. With distinction between generative classifier and discriminative classifier, we purpose to use some discriminative classifiers such as dual-form perceptron and kernelized support vector machine to improve to result of reasoning process. With capability of dual-form perceptron and kernelized support vector machine, finding linear or non-linear decision boundary for similarity-like supporting predicate for reasoning process.

关键词： Cognition Classification algorithms Support vector machines Logistics Kernel Training Training data

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Design of Flight Attitude control Model for the Mini-quadrotor

Design of Flight Attitude Control Model for the Mini-quadrot...

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IEEE International Conference on Mechatronics and Automation

作者： Ma Zhongli Li Huixin Li Qianqian Gu Yanming Li Zuoyong College of Automation Harbin Engineering University Heilongjiang 150001 China School of Astronautics Harbin Institute of Technology Heilongjiang 150001 China Fujian Provincial Key Laboratory of Information Processing and Intelligent Control Minjiang University Fuzhou 350121 China

ISBN: (纸本)9781509067602

Micro-quadrotor has recently been used in different areas even military field. However, controlling mini-quadrotor to flight attitude in the air has not been perfectly achieved due to mini-quad rotor's small size and light weight. The purpose of this paper is to introduce the flight attitude control system of mini-quadrotor, including design and simulation of calculations and controllers. By using distributed multi-sensors, the attitude and horizontal position information of mini-quadrotor is obtained. The simulation of the attitude controller is applied with the MATLAB Simulink library. In conclusion, the designed attitude controller can make mini-quadrotor have smooth flight and move in all directions and enable the mini-quadrotor to properly flight.

关键词： Mini-quadrotor Flight attitude control system Calculation controller

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An online state and parameter estimation of dynamic state space model of high speed train

International Journal of Control and Automation

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International Journal of control and Automation 2016年第9期9卷 51-62页

作者： Xie, Guo Zhang, Dan Hei, Xinhong Qian, Fucai Takahashi, Sei Nakamura, Hideo Xi'an University of Technology Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an Shaanxi710048 China College of Science and Technology Nihon University 7-24-1 Narashinodai Funabashi Chiba274-8501 Japan

In this paper, the state space model of high speed train is established to describe its nonlinear dynamic characteristics, whose parameters are disturbed by noise with an arbitrary distribution, and an online state and parameter identification method is proposed based on a parameters set by employing Bayesian theory and Particle Filter (PF). Firstly, the priori probabilities of all of the possible parameters are set to be equal, and the predicted states with different parameters are estimated using PF. Then the posterior probabilities of the parameters are updated by analyzing the characteristic of the measurement noise using Bayesian theory. Finally, the system sate and parameter are estimated by weighted summing all of the parameters and predicted states. The simulation results indicate that the proposed method can estimate the states and parameters of high speed train online and adaptively. © 2016 SERSC.

关键词： State space methods

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Stochastic Resonance of Asymmetric Bistable System Driven by Binary Signals under α Stable Noise 35

Stochastic Resonance of Asymmetric Bistable System Driven by...

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第35届中国控制会议

作者： JIAO Shang-bin KOU Jie LIU Ding ZHANG Qing National & Local Joint Engineering Research Center of Crystal Growth Equipment and System Integration Xi'an University of Technology Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing

ISBN: (纸本)9781509009107

In this paper the asymmetric bistable system excited by binary aperiodic signals is taken as a model and the average symbol error rate is regarded as an index to study stochastic resonance(SR) ***,the SR driven by binary signals under α stable noise is ***,the interplay between the α stable noise parameters α,β,and the system parameters a,b,r on the resonant output effect is *** results show that weak binary signals detection can be realized by adjusting the system parameters a,b and *** optimal values solved by these parameters can make the system produce the best SR *** a certain a or b,there is an optimal value under different α or β.For the parameter r,there is an optimal value under different α,and there are several optimal values under different β.Moreover,when α or β is given different values,the evolution laws in asymmetric bistable SR system excited by binary signals are *** results lay a foundation for realizing the adaptive parameter adjustment in asymmetric bistable SR system with α stable noise.

关键词： α stable noise asymmetric bistable system stochastic resonance symbol error rate

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Online Calibration of Intracortical Neural Interface Based on Transfer Learning

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Journal of Physics: Conference Series 2018年第1期1069卷

作者： Bo Peng Wei Li Jiping He School of Automation Huazhong University of Science and Technology Wuhan 430074 P. R. China Image Processing and Intelligent Control Key Laboratory of Education Ministry of China Wuhan 430074 P. R. China Department of Mechanical Engineering Beijing Institute of Technology Beijing 100081 P. R. China

In the application of neural interface, the neural activity of neurons and neuronal groups is not fixed even under the same task conditions. Meanwhile, the recording conditions of neural signals are also very unstable, with a high degree of within-and across-day variability. This results in a very unstable firing pattern for the recorded neural spike signals. In order to get better performance, the decoder often requires a lot of online calibration samples. This brings a heavy training burden to neural interface users. To solve this problem, this paper proposes to apply transfer learning (TL) to online calibration of intracortical neural interface to reduce the dependence of decoder on a large number of online calibration samples. Experimental results show that through transferring from a large amount of historical data, decoder can achieve satisfactory classification accuracy with only a small amount of online data.

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