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

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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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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Quantum-inspired immune clonal clustering algorithm based on watershed

Quantum-inspired immune clonal clustering algorithm based on...

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Congress on Evolutionary Computation

作者： Yangyang Li Nana Wu Jingjing Ma Licheng Jiao Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education of China Institute of Intelligent Information Processing and State Key Laboratory of Integrated Services Network Xidian University Xi'an China

Based on the concepts and principles of quantum computing, a novel clustering algorithm, called a quantum-inspired immune clonal clustering algorithm based on watershed (QICW), is proposed to deal with the problem of image segmentation. In QICW, antibody is proliferated and divided into a set of subpopulation groups. Antibodies in a subpopulation group are represented by multi-state gene quantum bits. In the antibody's updating, the quantum mutation operator is applied to accelerate convergence. The quantum recombination realizes the information communication between the subpopulation groups so as to avoid premature convergences. In this paper, the segmentation problem is viewed as a combinatorial optimization problem, the original image is partitioned into small blocks by watershed algorithm, and the quantum-inspired immune clonal algorithm is used to search the optimal clustering centre, and make the sequence of maximum affinity function as clustering result, and finally obtain the segmentation result. Experimental results show that the proposed method is effective for texture image and SAR image segmentation, compared with the genetic clustering algorithm based on watershed (W-GAC), and the k-means algorithm based on watershed (W-KM).

关键词： Clustering algorithms image segmentation Error analysis Radiative recombination Feature extraction Wavelet transforms Partitioning algorithms

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Symport/antiport P systems with look-ahead mode

Symport/antiport P systems with look-ahead mode

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International Conference on Bio-Inspired Computing: Theories and Applications, BICTA

作者： Yun Jiang Shuo Wang Jinbang Xu 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 Hubei China

The look-ahead is a forbidding condition formalized by a set of forbidden rules that are checked after all assignment of objects to rules are done. The look-ahead mode can decrease the inherent non-determinism of P systems and helps to the practical implementation of P systems on computers. In this work, the computational power of P systems with symport/antiport rules working in the look-ahead mode are investigated. Communication P systems with 3 membranes and the weight of symport and antiport rules being 2 and 1, respectively, working in the look-ahead mode, can recognize any recursively enumerable languages; a characterization of context-sensitive languages is obtained by communication P systems with 2 membranes working in the look-ahead mode.

关键词： Biomembranes Variable speed drives

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Upper limb rehabilitation robot integrated with motion intention recognition and virtual reality environment

Upper limb rehabilitation robot integrated with motion inten...

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作者： Wu, Jun Huan, Jian Wang, Yongji Key Laboratory of Image Processing and Intelligent Control Department of Control Science and Engineering Huazhong University of Science and Technology Wuhan 430074 China

ISBN: (纸本)9787894631046

Robotic-assisted therapy is of benefit to the recovery of upper limb motor function for the patients survived stoke. Whereas, there are few emphases on the patients' motion intention during the rehabilitation process. The goal of this study is to combine the control strategies based on patients' motion intention with an upper limb rehabilitation robot to improve the recovery for the patients. In this paper, we propose an integrated robot-assist rehabilitation system, in which a 3 degree-of-freedom (DOF) exoskeletal rehabilitation robot, an EMG-based intention recognition module and a VR game environment are seamlessly combined. According toharacteristics of EMG signals, the wavelet package analysis approach is applied to extract the features of EMG. The node energy is used to construct the feature vector instead of the original coefficients of wavelet package decomposition to resolve the time-invariance problem. Then feature projection results in the singularity problem of with-in scatter matrix during the feature dimension reduction. To overcome the disadvantage of the with-in scatter matrix, this paper uses a recursive algorithm which is proposed in our previous work. The reduced feature vector is recognized by a neural network classifier and the output of the classifier is used for the control inputs. Preliminary experiments are also performed to implement the control of the rehabilitation robotic system by using the proposed EMG reorganization method, together with a dart game realized in the virtual reality environment. Experimental results show that the performance of motion intention recognition is satisfactory and the entire integrated system is feasible.

关键词： Virtual reality

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Spectral representation of DNA sequences and its application

Spectral representation of DNA sequences and its application

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International Conference on Bio-Inspired Computing: Theories and Applications, BICTA

作者： Zhujin Zhang Lin Liu Jiuyong Li Zheng Zhang School of Computer and Information Science University of South Australia Adelaide SA Australia Key Laboratory of Image Processing and Intelligent Control Department of Control Science and Engineering Huazhong University of Science and Technology Wuhan China

Randić et al. proposed a famous spectral graphical representation of DNA sequences, and claimed that it avoids loss of information. In this paper we build two mathematical models for this graphical representation and prove that the claim is correct, and that it also avoids degeneracy. Moreover, we propose a new method to do similarity analysis of DNA sequences based on the spectral representation. The method adopts M value to characterize a graphical representation and uses 24-component vector as descriptor. The approach is illustrated on the complete coding sequence of beta-globin genes from 7 different species.

关键词： Humans Rabbits Mice Variable speed drives Silicon Sun Bovine

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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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International Conference on Bio-Inspired Computing: Theories and Applications, BICTA

作者： Zhujin Zhang Shuo Wang Xingyi Zhang Zheng Zhang School of Computer and Information Science University of South Australia Adelaide SA Australia Key Laboratory of Image Processing and Intelligent Control Department of Control Science and Engineering Huazhong University of Science and Technology Wuhan China Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education School of Computer Science and Technology Anhui University Hefei China

Randić et al. proposed a significant graphical representation for DNA sequences, which is very compact and avoids loss of information. In this paper, we build a fast algorithm for this graphical representation with time complexity O(n 2 ), and find another important advantage in the representation: no degeneracy. Moreover, we propose a new method to do similarity analysis of DNA sequences based on the representation. The approach adopts four elements of covariance matrix as a descriptor, and is illustrated on the first exon of beta-globin genes from 11 different species.

关键词： Rabbits Educational institutions Bovine Humans Sun DNA Mice

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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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