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International Conference on Industrial Mechatronics and Automation, ICIMA

作者： Jianguo Cao Liang Tao Department of Computer Science Anhui Vocational and Technical College of Industry and Trade Huainan China Key Laboratory of Intelligent Computing & Signal Processing Ministry of Education Anhui University Hefei China

ISBN: (纸本)9781424476534

Particle swarm optimization (PSO) is a recently proposed population-based random search algorithm, which performs well in some optimization problems. In this paper, we proposed an improved PSO algorithm to solve portfolio selection problems. The proposed approach IPSO employs an opposite mutation operator to enhance the performance of the standard PSO. In order to verify the performance of IPSO, we test it on five well-known benchmark function optimization problems. At last, we use IPSO to solve a classical portfolio selection problem. The results show that the proposed approach is effective and achieves better results than standard PSO.

关键词： Particle swarm optimization Portfolios signal processing algorithms Benchmark testing Artificial neural networks Computer industry educational institutions Genetic mutations Optimization methods Support vector machines

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Numerical Simulation of GPR based on 3-D High-order FDTD

Numerical Simulation of GPR based on 3-D High-order FDTD

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第九届国际天线、电波传播及电磁理论学术研讨会(ISAPE2010)

作者： Zhi-xiang Huang Hong-mei Du Yi-cai Mei Xin-gang Ren Xian-liang Wu Key Lab of Intelligent Computing & Signal Processing Anhui University Ministry of Education Hefei Department of Physics and Electronic Engineering Hefei Normal University Hefei China

The high-order finite-difference time-domain (HO-FDTD) technique is used in the simulation of ground-penetrating radar modeling in three dimensions (3-D), which can improve accuracy and reduce the error caused by numerical dispersion effectively. To absorb waves reflected from edges we implement convolutional perfectly matched layer (CPML) absorbing boundaries. It can efficiently absorb the reflections and greatly increase the computation efficiency. The surface-based reflection and cross-hole GPR modeling are simulated, and numerical results show the efficiency of the method.

关键词： Materials

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A Network-based Approach for Protein Functions Prediction Using Locally Linear Embedding

A Network-based Approach for Protein Functions Prediction Us...

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The 4th International Conference on Bioinformatics and Biomedical Engineering(第四届IEEE生物信息与生物医学工程国际会议 iCBBE 2010)

作者： Haifeng Zhao Dengdi Sun Rifeng Wang Bin Luo Key Lab of Intelligent Computing & Signal Processing of Ministry of Education School of Computer Science and Technology Anhui University Hefei 230039 P.R.China

Inferring protein functions from different data sources is a challenging task in the post-genomic era, as a large number of crude protein structures from structural genomics project are now solved without their biochemical functions characterized. Recently, many different methods have been used to predict protein functions including those based on Protein-Protein Interaction (PPI), structure, sequence relationship, gene expression data, etc. Among these approaches, methods based on protein interaction data are very promising. In this paper, we studied a network-based method using locally linear embedding (LLE). LLE is a robust learning algorithm that manipulates dimensionality reduction, neighborhood-preserving embedding for high-dimensional data. We first embed both annotated and unannotated proteins in a low dimensional Euclidean space;then, we apply semi-supervised learning techniques to classify unannotated proteins into different functional groups. Finally, we made predictions to the unknown functional proteins in yeast. 5-fold cross validation is then applied to the GO terms to compare the performance of different approaches, and the proposed method performs significantly better than the others.

关键词： Bioinformatics Semisupervised learning Genomics Protein sequence Gene expression Learning systems Sun intelligent networks intelligent structures Computer networks

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Inferring Protein Annotation from Topological Structural Analysis on Protein Interaction Network

Inferring Protein Annotation from Topological Structural Ana...

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The 4th International Conference on Bioinformatics and Biomedical Engineering(第四届IEEE生物信息与生物医学工程国际会议 iCBBE 2010)

作者： Dengdi Sun Jin Fan Haifeng Zhao Bin Luo Key Lab of Intelligent Computing & Signal Processing of Ministry of Education School of Computer Science and Technology Anhui University Hefei 230039 P.R.China

As more and more high-throughput protein-protein interactions data are collected, a large fraction of newly discovered proteins have an unknown functional role. A challenge to the scientific community is to assign these newly proteins with a biological function that can be verified by experiment. On the basis of thorough analysis of existing protein function prediction, we take double direction enumeration method combined with the distance constrains to find protein pathway, and propose a new predicting model based on topological structural of protein-protein interaction (PPI) network and protein pathway, which greatly increases the speed of the algorithm. To validate the method, the Yeast Saccharomyces cerevisiae protein-protein interaction network and corresponding protein pathways are analyzed. Comparing with other methods, our results can substantially improve the accuracy and robustness of functional annotation.

关键词： Proteins Fungi Databases Computer networks Biological system modeling Predictive models Organisms signal analysis Sun intelligent networks

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Predicting RNA secondary structure with Tabu Search

Predicting RNA secondary structure with Tabu Search

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IEEE International Conference on Cognitive Informatics

作者： Liu, Yongguo Hao, Jianrui Peng, Jun School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu 611731 China Key Laboratory of Intelligent Computing and Information Processing Ministry of Education Xiangtan University Xiangtan 411105 China College of Electronic Information Engineering Chongqing University of Science and Technology Chongqing 400050 China

ISBN: (纸本)9781424480401

In this paper, a novel method for predicting RNA secondary structure called RNA secondary structure prediction based on Tabu Search (RNATS) is proposed. In RNATS, two search models, intensification search and diversification search, are designed to exploit the local regions around the current solution and explore the unvisited space, respectively. Simulation experiments are conducted for six RNA sequences to show that the proposed method is feasible and effective. © 2010 IEEE.

关键词： Tabu search

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On Dynamic Weighting of Data in Clustering with K-Alpha Means

On Dynamic Weighting of Data in Clustering with K-Alpha Mean...

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International Conference on Pattern Recognition

作者： Si-Bao Chen Hai-Xian Wang Bin Luo Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education School of Computer Science and Technology Anhui University Hefei Anhui China Key Laboratory of Child Development and Learning Science of Ministry of Education Research Center of Learning Science South-East University Nanjing Jiangsu China

ISBN: (纸本)9781424475421

Although many methods of refining initialization have appeared, the sensitivity of K-Means to initial centers is still an obstacle in applications. In this paper, we investigate a new class of clustering algorithm, K-Alpha Means (KAM), which is insensitive to the initial centers. With K-Harmonic Means as a special case, KAM dynamically weights data points during iteratively updating centers, which deemphasizes data points that are close to centers while emphasizes data points that are not close to any centers. Through replacing minimum operator in K-Means by alpha-mean operator, KAM significantly improves the clustering performances.

关键词： Clustering algorithms Heuristic algorithms Indexes Partitioning algorithms signal processing algorithms Euclidean distance Iris

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Image denoising based on Non-Local means and multi-scale dyadic wavelet transform

Image denoising based on Non-Local means and multi-scale dya...

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International Conference on Computer Science and Information Technology (CSIT)

作者： Gang Yu Yong Yin Hongjun Wang Zhi Liu Dengwang Li School of Information science and engineering Shandong University Lin'an China Key Laboratory of Intelligent Computing & Information Processing Ministry of Education Xiangtan China

A variety of wavelet transform methods have been introduced to remove noise from images. However, many of these algorithms remove the fine details and smooth the structures of the image when removing noise. The wavelet coefficient magnitude sum (WCMS) algorithm can preserve edges, but it is at the expense of removing noise. The Non-Local means algorithm can removing noise effective. But it tend to cause distortion ( eg white). Meanwhile, when the noise is large, the method is not so effective. In this paper, we propose an efficient denoising algorithm. we denoised the image with non-local means algorithm in the spatial domain and WCMS algorithm in wavelet domain, weighted, combined them and got the image that we want. The experiment shows that our algorithm can improve PSNR form 0.6 dB to 1.0 dB and the image boundary is more clearly.

关键词： Discrete wavelet transforms Image edge detection PSNR Histograms Noise reduction

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CBCT image denoising based on multi-scale wavelet transform

CBCT image denoising based on multi-scale wavelet transform

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International Conference on BioMedical Engineering and Informatics (BMEI)

作者： Yong Yin Gang Yu Hongjun Wang Zhi Liu Dengwang Li School of Information science and engineering Shandong University Jinan China Key Laboratory of Intelligent Computing Information Processing of Ministry of Education Xiangtan China

Cone-Beam Computed Tomography (CBCT) has always been in the forefront of medical image processing. The denoising as a image pre-processing, has a great affected on the image analysis and recognition. In this paper, a new algorithm for image denoising was proposed. By thresholding the interscale wavelet coefficient magnitude sum(WCMS) within a cone of influence (COI), the wavelet coefficients are classified into 2 categories: irregular coefficients, and edge-related and regular coefficients. They are processed by different ways. Meanwhile according to the projection image sequences characteristics in CBCT system, an effective noise variance estimated methods was proposed. The experiment shows that our algorithm can improve PSNR form 1.3dB to 2.6dB, and the image border is more clearly.

关键词： Noise Wavelet coefficients Image reconstruction Classification algorithms Noise reduction Image edge detection Image denoising

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Teaching Reform and Innovation of the Course - Digital Image processing Experiments

Teaching Reform and Innovation of the Course - Digital Image...

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The 5th International Conference on Computer Science & education(第五届国际计算机新技术与教育学术研讨会 ICCSE'10)

作者： Haifeng Zhao Jin Tang Bin Luo Key Lab of Intelligent Computing & Signal Processing of Ministry of Education School of Computer Science and TechnologyAnhui UniversityHefei230039P. R. China

Digital image processing is an interdisciplinary course, which needs students have a strong background in mathematics. To help them change from passive learning to active learning, teaching reform and innovation of the course "Digital Image processing Experiments" is discussed in this paper. The combined platform of experiments includes TI DSP experimental box and three different kinds of programming languages. The six experimental projects cover the basic theories of digital image processing. The result can offer a significant reference for the teaching innovations in the other related specialties.

关键词： digital image processing:experimental teaching matlab:DSP

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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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