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Congress on Evolutionary Computation

作者： Ruochen Liu Zhengchun Shen Licheng Jiao Wei Zhang Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education of China Institute of Intelligent Information Processing Xidian University Xi'an China

Based on clonal selection principle and the immunodominance theory, a new immune clustering algorithm, Immunodomaince based Clonal Selection Clustering Algorithm (ICSCA) is proposed in this paper. An immunodomaince operator is introduced to the clonal selection algorithm, which can realize on-line gaining prior knowledge and sharing information among different antibodies. The proposed method has been extensively compared with Fuzzy C-means (FCM), Genetic Algorithm based FCM (GAFCM) and Clonal Selection Algorithm based FCM (CSAFCM) over a test suit of several real life datasets and synthetic datasets. The result of experiment indicates the superiority of the ICSCA over FCM, GAFCM and CSAFCM on stability and reliability for its ability to avoid trapping in local optimum.

关键词： Clustering algorithms Variable speed drives Immune system Partitioning algorithms Algorithm design and analysis Accuracy Immunity testing

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Clonal Selection Algorithm for image Compression

Clonal Selection Algorithm for Image Compression

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Congress on Evolutionary Computation

作者： Ruochen Liu Licheng Jiao Wei Zhang Jingjing Ma Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education of China Institute of Intelligent Information Processing Xidian University Xi'an China

Vector Quantization (VQ) is a useful tool for data compression and can be applied to compress the data vectors in the database. The quality of the recovered data vector depends on a good codebook. Mean/residual vector quantization (M/RVQ) has been shown to be efficient in the encoding time and it only needs a little storage. In this paper, Clonal Selection Algorithm for image Compression (CSAIC) is proposed. In CSAIC, Based on M/RVQ algorithm, an improved clonal selection algorithm is used to cluster the data of compressed images in order to obtain the optimal codebook. The proposed method has been extensively compared with Linde-Buzo-Gray(LBG), Self-Organizing Mapping (SOM) and Modified K-means(Mod-KM) over a test suit of seven natural images. The experimental results show that CSAIC outperforms other three algorithms in terms of image compression performance.

关键词： image coding Clustering algorithms Algorithm design and analysis Training Encoding Vector quantization

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A hybrid multiobjective immune algorithm with region preference for decision makers

A hybrid multiobjective immune algorithm with region prefere...

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Congress on Evolutionary Computation

作者： Licheng Jiao Wei Zhang Ruochen Liu Fang Liu Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education of China Institute of Intelligent Information Processing Xidian University Xi'an China

Recently, one of the main tools of decision maker (DM) preference incorporation in the multiobjective optimization (MOO) has been using reference points and achievement scalarizing functions (ASF). The core idea of these methods is converting the original multiobjective problem (MOP) into single objective problem by using ASF to find a single preferred point. However, many DMs not only interest in a single point but also a set of efficient points in their preferred region. In this paper, we introduce a hybrid multiobjective immune algorithm (HMIA) for DM. It combines the immune inspired algorithm and region preference based on a novel dominance concept called region-dominance without ASF. The new algorithm can let DMs flexibly decide the number of reference points and accurately determine the preferred region with its simple and effective interactive methods. To exemplify its advantages, simulated results of HMIA are shown with some well-known problems.

关键词： Delta modulation Neodymium Immune system Cloning Encoding Computational complexity

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Algorithm of Partition based Network Boosting for imbalanced data classification

Algorithm of Partition based Network Boosting for imbalanced...

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International Joint Conference on Neural Networks (IJCNN)

作者： Gou Shuiping Yang Hui Jiao Licheng Zhuang Xiong Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education of China and Institute of Intelligent Information Processing Xidian University Xi'an 710071 China

Network Boosting (NB) is an ensemble learning method which combines weak learners together based on a network and can learn the target hypothesis asymptotically. NB has higher generalization ability compared to Bagging and AdaBoost. But, when datasets are class-imbalanced, the performance of NB will decrease quickly. In order to solve this problem, we present a Partition based Network Boosting method (PNB) to classify imbalanced data. For PNB method, every classifier node of the classifier network is provided with the same number of training data which are all of same weights. The classifier in the network is built by the balanced training set sampled from the training data according to the weights record of the training data it holds. And then, the weights of the instances of every node classifier are updated based on the classification results of self-node and its neighbor nodes. The classifier network is trained repeatedly in such a way. Weight factor of hypothesis in the training progress is introduced to improve the performance. The final classification is formed by all the hypotheses of the classifier network learned during the training progress so that the label of new instances can be decided by the weight voting. The experimental results on UCI data and imbalanced biomedical data show that the PNB algorithm has better AUC and recall performance compared with NB learning machine.

关键词： Laboratories Impedance matching Breast Boosting Liver

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Study of high-resolution range profile for monostatic MIMO radar based on SIAR

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Xi Tong Gong Cheng Yu Dian Zi Ji Shu/Systems Engineering and Electronics 2010年第4期32卷 734-739+763页

作者： Zhao, Guang-Hui Chen, Bai-Xiao Gao, Zhao-Zhao Intelligent Perception and Image Understanding Key Lab of Ministry of Education of China Xidian Univ. Xi'an 710071 China National Key Lab for Radar Signal Processing Xidian Univ. Xi'an 710071 China National Information Control Laboratory Chengdu 610036 China

Conventional pulse compression use a periodical echo of single receive antenna, which is modulated by a certain carrier-frequency, in other words, single spectrum is exploited. But for MIMO radar, as the multi-carrier-frequency signals are transmitted simultaneously, if the spectrum of the target echo after channel separation can be combined to form the whole band spectrum echo, the corresponding range resolution can improve several times as compared with the conventional method, and it will be more convenient for follow-up detection and tracking. Considering the difference between the frequency modulation band and the interval between the adjacent frequencies, the spectrum joint after channel separation will be overlapped or spaced. The methods of spectrum moving of each echo and the spectrum extrapolation with Root-MUSIC algorithm are proposed, by which high-resolution range profile of the target is obtained. Simulation results verify the validity of these methods.

关键词： Multiple signal classification

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Numerical analysis of eddy current effect for low frequency electromagnetic method in cross-well

Numerical analysis of eddy current effect for low frequency ...

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International Conference on Computer Science & education (ICCSE)

作者： Song, Xi-Jin Guo, Bao-Long Dang, Rui-Rong Wang, Xue-Long Institute of Intelligent Control and Image Engineering Xidian University Xi'an China Key Laboratory of Photoelectric Logging and Detecting of Oil and Gas Ministry of Education Xi'an Shiyou University Xi'an China College of Computer Science and Technology Xi'an University of Technology Xi'an China

ISBN: (纸本)9781424460052

In order to analyze the eddy current caused by the excitation signal and its influence on the secondary field response, the general analytical expressions of eddy current density for low frequency electromagnetic in cross-well is deduced. Based on the axially symmetric time harmonic electromagnetic theory, this expression is established by Helmholtz equation of electric field in radial non-uniform formation. Eddy current density distribution of infinite homogeneous conductive medium and layered media in cross-well show that the metal casing has a strong absorption to electromagnetic signal and the frequency of the emission signal has important influence on its capability of penetrating the casing. The character of EMF (electromotive force)-frequency curves for the non magnetic high resistance formation demonstrates that the low frequency electromagnetic signal can penetrate the casing perfectly, and it also shows that response signal has the highest resolution to the formation resistivity while excited by the frequency about 200Hz. ©2010 IEEE.

关键词： Current density

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Matrix representation of spiking neural P systems

Matrix representation of spiking neural P systems

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11th International Conference on Membrane Computing, CMC 2010

作者： Zeng, Xiangxiang Adorna, Henry Martínez-Del-Amor, Miguel Ángel Pan, Linqiang Pérez-Jiménez, Mario J. Image Processing and Intelligent Control Key Laboratory of Education Ministry Department of Control Science and Engineering Huazhong University of Science and Technology Wuhan 430074 Hubei China University of the Philippines Diliman 1101 Quezon City Philippines Research Group on Natural Computing Department of Computer Science and Artificial Intelligence University of Sevilla Avda. Reina Mercedes s/n 41012 Sevilla Spain

ISBN: (纸本)3642181228

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. In this work, a discrete structure representation of SN P systems with extended rules and without delay is proposed. Specifically, matrices are used to represent SN P systems. In order to represent the computations of SN P systems by matrices, configuration vectors are defined to monitor the number of spikes in each neuron at any given configuration;transition net gain vectors are also introduced to quantify the total amount of spikes consumed and produced after the chosen rules are applied. Nondeterminism of the systems is assured by a set of spiking transition vectors that could be used at any given time during the computation. With such matrix representation, it is quite convenient to determine the next configuration from a given configuration, since it involves only multiplication and addition of matrices after deciding the spiking transition vector. © 2010 Springer-Verlag.

关键词： Vectors

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The method of image restoration in the environments of dust

The method of image restoration in the environments of dust

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International Conference on Mechatronics and Automation

作者： Wang, Yuanyu Li, Yuanzong Zhang, Tianxu Department of Computer Fundamental Education TaiYuan University of Technology TaiYuan CO 030024 China College of Mechanical Engineering TaiYuan University of Technology TaiYuan CO 030024 China Institute for Pattern Recognition and A.I. State Key Laboratory of Image Processing and Intelligent Control HuaZhong University of Science and Technology WuHan CO 430074 China

ISBN: (纸本)9781424451418

In order to solve the problem of image degradation caused by dust environments, an image degradation model considering multiple scattering factors caused by dust was first established using the first-order multiple scattering method. Then, a dark channel prior principle was applied to present an image restoration algorithm based on the image degradation model. Finally, a particle swarm optimization algorithm was applied to optimize the atmospheric light and the exposure parameters. This optimization algorithm was established according to the criterion of the image evaluation based on kirsch operator with dual threshold. By using the method an optimistic result of image restoration was obtained. The experimental results have shown that the method not only enhanced luminance and contrast, but also discovered more detail edges information. The method provided a foundation for target recognition in the dust environments. © 2010 IEEE.

关键词： Dust

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Object tracking in infrared image sequence by Monte-Carlo method

Object tracking in infrared image sequence by Monte-Carlo me...

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Congress on image and Signal processing, CISP

作者： Qianli Ma Min Wang Department of Control Science and Engineering Huazhong University of Science and Technology Wuhan China Image Processing and Intelligent Control Key Laboratory Educational Ministry of China Wuhan China

This paper presents a robust tracking algorithm for infrared objects in the image sequence, which is based on particle filer. Particle filter is a powerful tool for tracking especially in non-Gaussian condition, but the selection of samples is still a challenging problem. According to the frame-to-frame correlation, two basic assumptions are proposed. Borrowing the idea from Sequence Importance Sampling, Monte-Carlo method will be applied to solve the well-known shortcomings of Particle filter in this paper. Technologically, the proposed algorithm could also track multiple objects successfully. The experimental result has demonstrated its feasibility and validity.

关键词： Particle filters Monte Carlo methods Prediction algorithms Histograms Bayesian methods image sequences Signal processing algorithms

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Observer-based adaptive tracking control of rigid-link flexible-joint robot manipulators

Observer-based adaptive tracking control of rigid-link flexi...

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Chinese control Conference (CCC)

作者： Chao Liu Xianbo Xiang Philippe Poignet LIRMM French National Center for Scientific Research (CNRS) France Key Laboratory of Education Ministry for Image Processing and Intelligent Control Huazhong University of Science and Technology P.R. China

Joint flexibility is an important factor to consider in the robot control design if high performance is expected for the robot manipulators. Research works on control of rigid-link flexible-joint (RLFJ) robot in literature have assumed that the kinematics of the robot is known exactly. There have been few results that can deal with the kinematics uncertainty in RLFJ robot. In this paper, we propose an adaptive tracking control method which can deal with the kinematics uncertainty and uncertainties in both link and actuator dynamics of the RLFJ robot system. Nonlinear observers are designed to avoid accelerations measurement due to the fourth-order overall system dynamics. Asymptotic stability of the closed-loop system is shown and sufficient conditions are presented to guarantee the stability.

关键词： Equations Actuators Joints Kinematics Uncertainty Manipulator dynamics

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