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International Conference on Information and Automation (ICIA)

作者： Li Zhang Zhou Weida Ying Lin Licheng Jiao Institute of Intelligent Information Processing & Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education Xidian University Xi'an China

In this paper, a variant of support vector novelty detection (SVND) with dot product kernels is presented for non-spherical distributed data. Firstly we map the data in input space into a reproducing kernel Hilbert space (RKHS) by using kernel trick. Secondly we perform whitening process on the mapped data using kernel principal component analysis (KPCA). Finally, we adopt SVND method to train and test whitened data. Experiments were performed on artificial and real-world data.

关键词： Kernel Distributed databases Training Covariance matrix Support vector machines Training data Eigenvalues and eigenfunctions

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Improved Clonal Selection Algorithm based on Baldwinian Learning

Improved Clonal Selection Algorithm based on Baldwinian Lear...

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Congress on Evolutionary Computation

作者： Lining Zhang Maoguo Gong Licheng Jiao Jie Yang Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education of China Institute of Intelligent Information Processing Xidian University Xi'an China

In this paper, based on Baldwin effect, an improved clonal selection algorithm, Baldwin clonal selection algorithm, termed as BCSA, is proposed to deal with complex multimodal optimization problems. BCSA evolves and improves antibody population by three operations: clonal proliferation operation, Baldwinian learning operation and clonal selection operation. By introducing Baldwin effect, BCSA can make the most of experience of antibodies, accelerate the convergence, and obtain the global optimization quickly. In experiments, BCSA is tested on four types of functions and compared with the clonal selection algorithm and other optimization methods. Experimental results indicate that BCSA achieves a good performance, and is also an effective and robust technique for optimization.

关键词： Evolutionary computation

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Isomerous multiple classifier ensemble method with SVM and KMP

Isomerous multiple classifier ensemble method with SVM and K...

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International Conference on Audio, Language and image processing, ICALIP

作者： Shuiping Gou Shasha Mao Licheng Jiao Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education of China Institute of Intelligent Information Processing Xidian University Xi'an China

A method for multi-classifier ensemble of Support Vector Machine ensemble (SVMs) and Kernel Matching Pursuit Ensemble (KMPs) is proposed. Support Vector Machine has advantage in solving classification problem of high dimension and small size dataset, and Kernel Matching Pursuit has almost classified performance and the more sparsely solution as comprised with the SVM. So the SVM and the KMP are mix boosted in this paper, which can decrease generalization errors of the single classifier ensemble and improve ensemble classification accuracy by increasing diversity between ensemble individuals. The experiments show that the proposed method can shorten running time and improve classification accuracy compared with individual SVMs or KMPs.

关键词： Support vector machines Classification algorithms Accuracy Kernel Training Matching pursuit algorithms Machine learning

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Support vectors pre-extracting for support vector machine based on K nearest neighbour method

Support vectors pre-extracting for support vector machine ba...

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International Conference on Information and Automation (ICIA)

作者： Li Zhang Ning Ye Weida Zhou Licheng Jiao Institute of Intelligent Information Processing & Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education University of Xidian Xi'an Shaanxi China

Support vector machine, a universal method for learning from data, gains its development based on statistical learning theory. It shows many advantages in solving nonlinearly small sample and high dimensional problems of pattern recognition. Only a part of samples or support vectors (SVs) plays an important role in the final decision function. But SVs could not be obtained in advance until a quadratic programming is performed. In this paper, we use K-nearest neighbour method to extract a boundary vector set which may contain SVs. The number of the boundary set is smaller than the whole training set. Consequently it reduces the training samples, speeds up the training of support vector machine.

关键词： Training Support vector machines Kernel Distance measurement Classification algorithms Polynomials Support vector machine classification

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Lossy to lossless image compression based on reversible integer DCT

Lossy to lossless image compression based on reversible inte...

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IEEE International Conference on image processing

作者： Lei Wang Jiaji Wu Licheng Jiao Li Zhang Guangming Shi Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education of China Institute of Intelligent Information Processing Xidian University Xi'an China

A progressive image compression scheme is investigated using reversible integer discrete cosine transform (RDCT) which is derived from the matrix factorization theory. Previous techniques based on DCT suffer from bad performance in lossy image compression compared with wavelet image codec. And lossless compression methods such as IntDCT, I2I-DCT and so on could not compare with JPEG-LS or integer discrete wavelet transform (DWT) based codec. In this paper, lossy to lossless image compression can be implemented by our proposed scheme which consists of RDCT, coefficients reorganization, bit plane encoding, and reversible integer pre- and post-filters. Simulation results show that our method is competitive against JPEG-LS and JPEG2000 in lossless compression. Moreover, our method outperforms JPEG2000 (reversible 5/3 filter) for lossy compression, and the performance is even comparable with JPEG2000 which adopted irreversible 9/7 floating-point filter (9/7F filter).

关键词： image coding Discrete cosine transforms Transform coding Filters Performance loss Discrete wavelet transforms Codecs image reconstruction Laboratories Information processing

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Optimal Approximation of Linear Systems by an Improved Clonal Selection Algorithm

Optimal Approximation of Linear Systems by an Improved Clona...

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Congress on Evolutionary Computation

Based on the theory of clonal selection in immunology, by introducing Baldwin effect, an improved clonal selection algorithm, termed as Baldwin clonal selection algorithm (BCSA), is proposed to solve the optimal approximation of linear systems. For engineering computing, the novel algorithm adopts three operations to evolve and improve the population: clonal proliferation operation, Baldwinian learning operation and clonal selection operation. The experimental study on the optimal approximation of a stable linear system and an unstable one show that the approximate models searched by the new algorithm have better performance indices than those obtained by some existing algorithms including the differential evolution algorithm, multi-agent genetic algorithm and artificial immune response algorithm.

关键词： Evolutionary computation

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Improved Clonal Selection Algorithm based on Lamarckian Local Search Technique

Improved Clonal Selection Algorithm based on Lamarckian Loca...

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Congress on Evolutionary Computation

作者： Jie Yang Maoguo Gong Licheng Jiao Lining 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

In this paper, we introduce Lamarckian learning theory into the clonal selection algorithm and propose a sort of Lamarckian clonal selection algorithm, termed as LCSA. The major aim is to utilize effectively the information of each individual to reinforce the exploitation with the help of Lamarckian local search. Recombination operator and tournament selection operator are incorporated into LCSA to further enhance the ability of global exploration. We compared LCSA with the clonal selection algorithm (CSA) in solving twenty benchmark problems to test the performance of LCSA. The results demonstrate that LCSA is effective and efficient in solving numerical optimization problems.

关键词： Artificial neural networks Immune system Cloning Optimization Evolutionary computation Benchmark testing Interpolation

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Sensing environment with mobile robot by applying fuzzy-extended DSmT

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Huazhong Keji Daxue Xuebao (Ziran Kexue Ban)/Journal of Huazhong University of Science and Technology (Natural Science Edition) 2008年第SUPPL. 1期36卷 113-115页

作者： Li, Xinde Huang, Xinhan Dai, Xianzhong Meng, Zhengda Key Laboratory of Image Processing and Intelligent Control Southeast University Nanjing 210096 China Department of Control Science and Engineering Huazhong University of Science and Technology Wuhan 430074 China

Dezert-smarandache theory (DSmT) was extended with fuzzy theory by considering the different Fuzzy T-norm operators, in order to develop a more general and flexible combinational rule for more extensive application. At the same time, fuzzy-extended DSmT was applied to mobile robot's sensing environment with the help of new self-localization method based on δ neighboring field appearance matching and also the perception effect was compared with different T-norm operators. Finally, an effective approach to solv sensing fusion of uncertainty environment was found.

关键词： Mobile robots

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A Particle Filtering Algorithm for Tracking Moving Target under Clutter

A Particle Filtering Algorithm for Tracking Moving Target un...

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7th World Congress on intelligent Control and Automation (WCICA 2008), vol.13

作者： Guocheng Liu Yongji Wang Chinese Education Ministry Key Laboratory for Image Processing & Intelligent Control Huazhong University of Science and Technology Wuhan China

On visual tracking, a particle filter algorithm was presented to track a moving target under clutter environment which can deal with rotation, scale changes, variations in the light source and partial occlusions. So it can track the target with robustness. The proposed method was based on particle filter, integrated with color histogram in the measurement model, and the system model was second order autoregressive process. The algorithm took into account the latest observations and the tracked target can be rigid or non-rigid. Also the method can run in real-time. The experimental results confirm that the method is effective even when the monocular camera is moving and the target object is partially occluded in a clutter background.

关键词： Particle filter Visual tracking Color histogram

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Co-scheduling model and algorithm of the three gorges-gezhou dam based on GA

Co-scheduling model and algorithm of the three gorges-gezhou...

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7th World Congress on intelligent Control and Automation (WCICA 2008), vol.10

作者： Xiaoping Wang Huan Qi Henghui Xiao Xiaopan Zhang Key Laboratory of Image Processing and Intelligent Control Institute of Systems Engineering Huazhong University of Science and Technology Wuhan China

This paper provided a mathematic model for Three Gorges-Gezhou dam co-scheduling problems, based on full analysis of Three Gorges-Gezhou dam's actual needs, to maximize the total throughput of Three Gorges-Gezhou dam, to maximize the utilization ratio of shiplock area and minimize the total navigation shiplock waiting time under eight constraint conditions. Then a scheduling algorithm based on GA was pointed out. The three gorges south lock, Gezhou dam lock, the three gorges north lock were optimization searched separately in the GA algorithm. The scheduling results of the three gorges south lock were taken as the origin of the whole plan period, and also were taken as the basis of the Gezhou dam scheduling together with the ship applied information. The scheduling results of Gezhou dam were regarded as the basis of the three gorges north lock scheduling together with the ship applied information, so repeated, until the optimal scheduling results were given, or the most iterative step was reached. The applied result shows that making a period plan of two dam five lock only needs 2 minutes, and the plan is quite effective according to practical application.

关键词： Genetic algorithm The three gorges-gezhou dam Co-scheduling Mathematical model

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