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Uniform Solution to QSAT by P Systems with Proteins

电子学报(英文版) 2012年第4期21卷 667-672页

作者： LU Chun SHI Xiaolong Key Laboratory of Image Processing and Intelligent Control Department of Control Science and Engineering Huazhong University of Science and Technology Wuhan 430074 China

P systems are distributed parallel computing models in the area of membrane computing, which are inspired by the structure and the functioning of living cells, as well as the organization of cells in tissues, organs, and other higher order structures. P systems with proteins on membranes are a class of P systems, which have proved to be very efficient computing devices. Specifically, it was known that the Quantified satisfiability problem (QSAT) of a Boolean formula can be solved by a semi-uniform family of P systems with proteins on membranes and with membrane division. However, it remains open whether a uniform families of P systems with proteins on membranes can solve in polynomial time exactly the class of problems PSPACE. In this work, we present a uniform solution to QSAT problem by P systems with proteins on membranes in a linear time with respect to both the number n of Boolean variables and the number m of clauses of the instance, which answers the above open problem.

关键词：蛋白质膜 P系统分布式并行计算多项式时间 PSPACE 高级结构细胞膜计算模型 Membrane computing, Membrane protein, PSPACE-complete problem, Quantified satisflability problem （QSAT problem）, Uniform solution.

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Flocking in Multi-Agent Systems with Multiple Virtual Leaders Based Only on Position Measurements

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Communications in Theoretical Physics 2012年第5期57卷 801-807页

作者：苏厚胜 Department of Control Science and Engineering Image Processing and Intelligent Control Key Laboratory of Education Ministry of ChinaHuazhong University of Science and Technology

Most existing flocking algorithms assume one single virtual leader and rely on information on both relative positions and relative velocities among neighboring *** this paper,the problem of controlling a flock of mobile autonomous agents to follow multiple virtual leaders is investigated by using only position information in the sense that agents with the same virtual leader asymptotically attain the same velocity and track the corresponding virtual leader based on only position measurements.A flocking algorithm is proposed under which every agent asymptotically attains its desired velocity,collision between agents can be avoided,and the final tight formation minimizes all agents' global potentials.A simulation example is presented to verify and illustrate the theoretical results.

关键词： distributed control flocking multi-agent system multiple virtual leaders

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Small Universal Sequential Spiking Neural P Systems based on Minimum Spike Number

Small Universal Sequential Spiking Neural P Systems based on...

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The Second Asian Conference on Membrane Computing(ACMC2013)

作者： Keqin Jiang Yufang Huang Jinbang Xu Zhihua Chen Key Laboratory of Image Processing and Intelligent Control School of Automation Huazhong University of Science and Technology School of Computer and Information Anqing Normal University College of Mathematics Southwest Jiaotong University

Spiking neural P systems (SN P systems, for short) are a class of distributed parallel computing devices inspired from the way neurons communicate by means of spikes. Recently, a variant of SN P systems was considered: at each step the neuron with the minimum number of spikes among the neurons that can spike will fire. In previous literature, it was obtained that such systems can achieve Turing completeness when the computing result is realized through accumulation of spikes in the output neuron. In this work, we use a natural way to define the computing result of the systems, by means of determining the time interval between the first two spikes emitted by the output neuron. As devices of computing functions, we construct a universal sequential SN P system based on minimum spike number (without delay) by using 137 neurons;as generators of sets of numbers, a universal sequential SN P system based on minimum spike number (without delay) with 126 neurons is also obtained.

关键词： Membrane computing, Spiking neural P system, Sequentiality, Small universal system

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CROSS-VIEW ACTION RECOGNITION VIA TRANSDUCTIVE TRANSFER LEARNING

CROSS-VIEW ACTION RECOGNITION VIA TRANSDUCTIVE TRANSFER LEAR...

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IEEE International Conference on image processing

作者： Jie Qin Zhaoxiang Zhang Yunhong Wang Laboratory of Intelligent Recognition and Image Processing Beijing Key Laboratory of Digital Media School of Computer Science and Engineering Beihang University Beijing 100191 China

ISBN: (纸本)9781479923427

Human action recognition is a hot topic in computer vision field. Various applicable approaches have been proposed to recognize different types of actions. However, the recognition performance deteriorates rapidly when the viewpoint changes. Traditional approaches aim to address the problem by inductive transfer learning, in which target-view samples are manually labeled. In this paper, we present a novel approach for cross-view action recognition based on transduc-tive transfer learning. We address the problem by transferring instances across views. In our settings, both labels of examples from the target view and the corresponding relation between examples from pairwise views are dispensable. Experimental results on the IXMAS multi-view data set demonstrate the effectiveness of our approach, and are comparable to the state of the art.

关键词： action recognition transfer learning transductive SVM Transfer (Psychology) state of the art target view Recognition (Psychology) Learning

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SEMI-SUPERVISED LEARNING IN TRAFFIC SCENE SURVEILLANCE BASED ON LABEL-PROPAGATION

SEMI-SUPERVISED LEARNING IN TRAFFIC SCENE SURVEILLANCE BASED...

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IEEE International Conference on image processing

作者： Meng Liang Zhaoxiang Zhang Yunhong Wang Laboratory of Intelligent Recognition and Image Processing Beijing Key Laboratory of Digital Media School of Computer Science and Engineering Beihang University Beijing 100191 China

ISBN: (纸本)9781479923427

Object classification in traffic scene surveillance has attracted much attention recent years. Traditional classification methods need lots of labeled samples to build a satisfying classifier. However, the acquisition of the labeled samples may cost lots of time and human labor. In this paper, we propose an label-propagation based semi-supervised learning method which uses the information of both labeled and unlabeled samples. Experiment results show that our method outperforms the traditional methods both in accuracy and robustness.

关键词： traffic scene surveillance object classification label propagation semi-supervised learning Semi-supervised Learning Traffic traffic monitoring Classification Methods

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The impact of stock-dependent demand on supply chain dynamics

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Applied Mathematical Modelling 2013年第18-19期37卷 8348-8362页

作者： Yongchang Wei Hongwei Wang Chao Qi Institute of Systems Engineering and the Key Laboratory of Image Processing and Intelligent Control of Education Ministry Huazhong University of Science and Technology Wuhan 430074 PR China School of Business Administration Zhongnan University of Economics and Law Wuhan 430073 PR China

This paper presents an investigation on the dynamics of a supply chain system under stock-dependent demand. Considering the feature of piecewise linearity, a switched linear model composed of three subsystems is developed. Based on the switched model, some analytical stability results are derived. Simulation experiments are designed to verify the stability results and observe nonlinear dynamics. We show that stock-dependent demand not only leads to different stability results but also makes nonlinear dynamics more complicated. We also reveal that the nonlinear dynamics of the switched model, such as chaotic and periodic fluctuations of inventory and order, are essentially caused by switching frequently among subsystems due to uncertainties of inventory status. The results obtained in this paper help us understand the dynamic complexities of supply chain system and provide guidelines for selecting decision parameters to improve overall performance.

关键词： Supply chain system Stock-dependent demand Dynamics Switched system Modeling and simulation

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RLSESN-based PID adaptive control for a novel wearable rehabilitation robotic hand driven by PM-TS actuators

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International Journal of intelligent Computing and Cybernetics 2012年第1期5卷 91-110页

作者： Jun Wu Jian Huang Yongji Wang Kexin Xing Key Laboratory of Image Processing and Intelligent Control Department of Control Science and EngineeringHuazhong University of Science and TechnologyWuhanChina

Purpose-The purpose of this paper is to develop a novel wearable rehabilitation robotic hand driven by Pneumatic Muscle-Torsion Spring(PM-TS)for finger *** has complex nonlinear dynamics,which makes PM modelling *** realize high-accurate tracking for the robotic hand,an Echo State Network(ESN)-based PID adaptive controller is proposed,even though the plant model is ***/methodology/approach-To drive a single joint of rehabilitation robotic hand,the paper proposes a new PM-TS actuator comprising a Pneumatic Muscle(PM)and a Torsion Spring(TS).Based on the novel actuator,a wearable robotic hand is *** employing the model-free approximation capability of ESN,the RLSESN based PID adaptive controller is presented for improving the trajectory tracking performance of the rehabilitation robotic *** ESN together with Recursive Least Square(RLS)is called a RLSESN,where the ESN output weight matrix is updated by the online RLS learning ***–Practical experiments demonstrate the validity of the PM-TS actuator and indicate that the performance of the RLSESN based PID adaptive controller is better than that of the conventional PID *** addition,they also verify the effectiveness of the proposed rehabilitation robotic ***/value–A new PM-TS actuator configuration that uses a PM and a torsion spring for bi-directional movement of joint is *** utilizing the new PM-TS actuator,a novel wearable rehabilitation robotic hand for finger therapy is *** on the unknown plant model,the RLSESN_PID controller is proposed to attain satisfactory performance.

关键词： Robotics control systems controllers Actuators Adaptive system theory Wearable rehabilitation robotic hand Echo state network Pneumatic muscle Trajectory tracking

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Displacement prediction of landslide based on PSOGSA-ELM with mixed kernel

Displacement prediction of landslide based on PSOGSA-ELM wit...

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International Workshop on Advanced Computational Intelligence (IWACI)

作者： Cheng Lian Zhigang Zeng Wei Yao Huiming Tang School of Automation Key Laboratory of Image Processing and Intelligent Control of Education Ministry China School of Computer Science South-Central University for Nationalities Wuhan China Faculty of Engineering China University of Geosciences Wuhan China

The prediction of landslide displacement is essential for carrying out to improve the disaster warning system and reduce casualties and property losses. This study applies a novel neural network technique, extreme learning machine (ELM) with kernel function, to landslide displacement prediction problem. However, the generalization performance of ELM with kernel function depends closely on the kernel types and the kernel parameters. In this paper, we use a convex combination of Gaussian kernel function and polynomial kernel function in ELM, which may use these two types of kernel functions' advantages. In order to avoid blindness and inaccuracy in parameter selection, a novel hybrid optimization algorithm based on the combination of Particle Swarm Optimization (PSO) and Gravitational Search Algorithm (GSA) is used to optimize the regularization parameter C, the Gaussian kernel parameter γ, the polynomial kernel parameter q and the mixing weight coefficient η. The performance of our model is verified through two case studies in Baishuihe landslide and Yuhuangge landslide.

关键词： Kernel Terrain factors Optimization Hazards Reservoirs Training Support vector machines

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pNovo+: De Novo Peptide Sequencing and Assembly Using Complementary HCD and ETD Tandem Mass Spectra

pNovo+: De Novo Peptide Sequencing and Assembly Using Comple...

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第八届中国蛋白质组学大会

作者： Hao Chi Haifeng Chen Kun He Long Wu Bing Yang Rui-Xiang Sun Jianyun Liu Wen-Feng Zeng Chun-Qing Song Si-Min He Meng-Qiu Dong Key Lab of Intelligent Information Processing Institute of Computing TechnologyChinese Academy of SciencesBeijing 100190China National Institute of Biological SciencesBeijingBeijing 102206China Laboratory of Intelligent Recognition and Image ProcessingBeijing Key Laboratory of Digital MediaBeihang UniversityBeijing100191China

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A uniform solution to the independent set problem through tissue P systems with cell separation

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Frontiers of Computer Science 2012年第4期6卷 477-488页

作者： Xingyi ZHANG Xiangxiang ZENG Bin LUO Zheng ZHANG Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education School of Computer Science and TechnologyAnhui UniversityHefei 230039China Department of Computer Science Xiamen UniversityXiamen 361005China Key Laboratory of Image Processing and Intelligent Control Department of Control Science and EngineeringHuazhong University of Science and TechnologyWuhan 430074China

Membrane computing is an emergent branch of natural computing, which is inspired by the structure and the functioning of living cells, as well as the organization of cells in tissues, organs, and other higher order structures. Tissue P systems are a class of the most investigated computing mod- els in the framework of membrane computing, especially in the aspect of efficiency. To generate an exponential resource in a polynomial time, cell separation is incorporated into such systems, thus obtaining so called tissue P systems with cell separation. In this work, we exploit the computational efficiency of this model and construct a uniform family of such tissue P systems for solving the independent set problem, a well-known NP-complete problem, by which an efficient so- lution can be obtained in polynomial time.

关键词： membrane computing tissue P system cell sep- aration independent set problem

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