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Shiyou Huagong Gaodeng Xuexiao Xuebao/Journal of Petrochemical Universities 2008年第4期21卷 87-90页

作者： Xu, Qin Tao, Liang MOE Key Laboratory of Intelligence Computing and Signal Processing Anhui University Hefei 230039 China

A fast algorithm for computing analysis window of real discrete Gabor transforms based on DCT in order to realize real discrete Gabor transforms efficiently was introduced. The original biorthogonal condition expression of computing analysis window functions was predigested by using the orthogonality of discrete cosine functions, and then divided the original equations set into a set of independent subsystems. Thus this algorithm can save a considerable computation. Some numerical experiments were given to demonstrate the efficiency and advantages of the proposed algorithm. It decreases the computational time compared to the original algorithm.

关键词： Analysis window DCT Real discrete Gabor transforms (RDGT)

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Model of granular computing

Model of granular computing

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2008 International Conference on Theoretical and Mathematical Foundations of Computer Science, TMFCS 2008

作者： Zhao, Liquan Zhang, Ling Province Key Laboratory of Electronic Business Nanjing University of Finance and Economics Nanjing 210003 China Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education Anhui University Hefei 230039 China Artificial Intelligence Institute Anhui University Hefei 230039 China

ISBN: (纸本)9781615677207

Granular computing which imitates the manner of human thinking is a mathematical tool to deal with incomplete, uncertain, imprecise and inconsistent knowledge. Just as a great umbrella, it may be regarded as a label of theories, methodologies, techniques and tools about granules, mainly including fuzzy set theory, rough set theory and quotient space theory. In this paper we discuss the relationship of three theories. Then we introduce a general model of granular computing and present a macrocosmic (microcosmic) hierarchical representation of granules.

关键词： Rough set theory

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An Efficient Method for Sampling and Computing Molecular Surface

An Efficient Method for Sampling and Computing Molecular Sur...

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International Conference on BioMedical Engineering and Informatics (BMEI)

作者： Junping Xiang Maolin Hu Key Laboratory of Intelligent Computing & Signal Processing Ministry of Education and School of Mathematics and Computational Science Anhui University China

An atom-centered protocol based method for surface sampling in grid space is proposed. Van der Waals, solvent-accessible and solvent-excluded surface can be generated in a unified framework. A spherical hash function is used to mark whether the points are inside a sphere, and the hash tables are used to record which spheres the surface points locate on. The proposed method can be modified to apply in the parallel computation directly, which is useful for molecular dynamics simulation, docking and surface comparison and so on. Our tests indicate that the proposed method is efficient and the generated surfaces are suitable for quantitative analysis and visualization.

关键词： Sampling methods Synthetic aperture sonar Solvents Atomic measurements Grid computing Probes Biomedical computing signal sampling Concurrent computing Visualization

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Comparisons of Protein Structure Alignment Methods: Rigid and Flexible, Sequential and Non-Sequential

Comparisons of Protein Structure Alignment Methods: Rigid an...

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International Conference on Bioinformatics and Biomedical Engineering (ICBBE)

作者： Junping Xiang Maolin Hu Key Laboratory of Intelligent Computing & Signal Processing Ministry of Education School of Mathematics and Computational Science Anhui University Hefei Anhui China

We try to evaluate the sequential and non-sequential and flexible structural alignment methods on SCOP 1.71. Firstly, we compare the flexible method with rigid methods and compare the sequence order dependent methods with sequence order independent methods by two typical cases. Secondly, the performances of the above methods are evaluated using ten protein pairs which are considered as "hard to detect" similarities. Thirdly, we evaluate the methods by comparing the ROC curves based on their native score and geometric measure Qscore. Then we compare the methods directly using geometric match measure Qscore, which also allows the creation of a 'Best- of-All' method. The main conclusions are: (1) we find that the best alignments found by sequential methods are more consistent with the SCOP classification; (2) we show that ROC curves are of limited value and that their ranking of the methods is not consistent with the ranking implied by the quality of the alignments the methods find; (3) we also find that the alignments of flexible method and non-sequential methods are better than the corresponding alignments of rigid sequential method from the viewpoint of geometric superposition, and flexible method and non-sequential methods can find more cross-fold similarities.

关键词： Proteins Gold Performance evaluation Amino acids Fasteners Laboratories computational intelligence Intelligent structures Biomedical signal processing Educational programs

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A REDUNDANT INCREMENTAL LEARNING ALGORITHM FOR SVM

A REDUNDANT INCREMENTAL LEARNING ALGORITHM FOR SVM

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2008 International Conference on Machine Learning and Cybernetics(2008机器学习与控制论国际会议)

作者： WEN-JIAN WANG School of Computer and Information Technology Key Laboratory of Computational Intelligence & Chinese Information Processing of Ministry of Education Shanxi University Taiyuan P.R.China 030006

This paper presents an improved incremental learning technique for SVM, namely redundant incremental SVM (RISVM), for pattern classification problems. Through adding some non-support vectors (say, redundant vectors in the sense of contribution to the final solution) at each incremental step, the RISVM algorithm can achieve similar performance to the SVM in batch (or non-incremental SVM) but result in less support vectors for the same quality of pattern classification, and also it can provide better generalization performance in comparison with other incremental techniques for SVM. The bispiral problem and five widely used benchmark data sets are employed to verify the method, and the simulations support the feasibility and effectiveness of the proposed approach.

关键词： Classification Incremental learning Redundant vector Support vector machine

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Granulation Operators on a Knowledge Base

Granulation Operators on a Knowledge Base

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International Conference on Granular Computing

作者： Yuhua Qian Jiye Liang Wei Wei Key Laboratory of Computational Intelligence and Chinese Information Processing of Ministry of Education Taiyuan 030006 Shanxi China School of Computer and Information Technology Shanxi University Taiyuan 030006 Shanxi China

ISBN: (纸本)9781424425129

Knowledge in knowledge bases have two categories: complete and incomplete. In this paper, through uniformly expressing these two kinds of knowledge, we first address four operators on a knowledge base, which are adequate for generating new knowledge through using known knowledge. Then, we establish the relationship between knowledge and knowledge granulation. These results will be very helpful for knowledge discovery from knowledge bases and play a significant role for establishing a framework of granular computing in knowledge bases.

关键词： Granular computing Rough set theory Knowledge base Granulation operator

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Measurement of granules

Measurement of granules

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IEEE International Conference on Cognitive Informatics

作者： Liquan Zhao Ling Zhang Province Key Laboratory of Electronic Business Nanjing University of Finance and Economics Nanjing China Artificial Intelligence Institute Anhui University Hefei China Key Laboratory of Intelligent Computing & Signal Processing of Ministry of Education Anhui University Hefei 230039 China

ISBN: (纸本)9781424425389

The measurement of granules is the most foundational problem in granular computing. The paper is intended to study the measurement of granules on a finite or infinite set. For a finite set we discuss the measurement of granules corresponding to an equivalence relation on a finite set and introduce a definition of conditional granularity in order to distinguish those granules with the same granularity. For an infinite set we can define different granularity in different questions, but we give the basic idea of granularity, that is, the granularity of a granule is the sum of the relative information contents of its atomic granules.

关键词： Micro hierarchical tree Macro hierarchical figure Granularity Conditional granularity grain size Equivalence relation infinite set Finite Infinite

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Multiword Expression Recognition Using Multiple Sequence Alignment

Multiword Expression Recognition Using Multiple Sequence Ali...

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International Conference on Advanced Language processing and Web Information Technology (ALPIT)

作者： Ru Li Lijun Zhong Jianyong Duan School of Computer and Information Technology Shanxi University Taiyuan Shanxi China Chinese Information Processing of Ministry of Education Key Laboratory of Computational Intelligence Taiyuan Shanxi China Computer Science and Engineering North-China University of Technology Beijing China

For the Multiword Expression (MWE) recognition, the Multiple Sequence Alignment (MSA) is proposed on the motivation of gene recognition. Because textual sequence is similar to gene sequence in pattern analysis. This MSA technique is combined with error-driven rules, with the improved efficiency beyond the traditional *** provides a guarantee for the MWE recall. It uses the dynamic programming method to prevent candidates from combinational explosion, and provides a global solution for pattern extraction instead of sub-pattern redundancy. Consequently, it has accurate measures for flexible patterns. In experiment, some advanced statistical measures are performed for ranking candidates. In the comparison experiment, the MSA approach achieved better results.

关键词： Feature extraction Data mining Dynamic programming Noise Information filters Information filtering Statistical analysis

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Learning methods of constructive neural network

Learning methods of constructive neural network

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2007 International Conference on Artificial intelligence and Pattern Recognition, AIPR 2007

ISBN: (纸本)9781615677214

Learning methods of constructive neural network aims to overcome the disadvantages of BP algorithm, which has many advantages such as fast convergent rate, less computation, good fault-tolerant and strong generalization ability, etc. Its structure is constructed step by step in the processing of the data rather than being prescribed in advance. This paper mainly introduces the developing motivations, research status quo and development directions, laying stress on two kinds of constructive learning methods: FP algorithm and covering algorithm. After discussing the construction and basic properties of FP network, we construct an FP network as a general clustering unit, and analyze its main properties. On the base of summarizing covering algorithm we present a general neighborhood covering algorithm and its corresponding network. According to the characteristics of the algorithm we analyze its existing problems and propose the further research orientations.

关键词： Pattern recognition

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Multifractal and R/S Analysis of Protein Structure

Multifractal and R/S Analysis of Protein Structure

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ACIS International Conference on Software Engineering, Artificial intelligence, Networking, and Parallel/Distributed Computing (SNPD)

作者： Zheng Tingting Cheng Jiaxing Mao Junjun Song Jie Key Laboratory of intelligent Computing & Signal Processing School of mathematics and computational science Anhui University Hefei China Key Laboratory of intelligent Computing & Signal Processing Anhui University Hefei China School of mathematics and computational science Anhui University Hefei China

The spacing distance of amino acids is used to study the relationship between the primary structure and structural classification of large proteins. Rescaled-range (R/S) analysis was adopted to examine long-range correlation property of proteins. And multifractal property is then discussed by the spacing distance of amino acids. A classification of proteins by assigning to each sequence a point in two-dimensional space (Aa,H) is given to construct a phylogenetic tree. This result is shown to be reasonably satisfactory to alpha + beta class.

关键词： Fractals Proteins Sequences Amino acids Mathematics Hidden Markov models Rivers Software engineering Artificial intelligence Distributed computing

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