One-class support vector machine （OCSVM） and support vector data description （SVDD） are two main domain-based one-class （kernel） classifiers. To reveal their relationship with density estimation in the case of t...One-class support vector machine （OCSVM） and support vector data description （SVDD） are two main domain-based one-class （kernel） classifiers. To reveal their relationship with density estimation in the case of the Gaussian kernel, OCSVM and SVDD are firstly unified into the framework of kernel density estimation, and the essential relationship between them is explicitly revealed. Then the result proves that the density estimation induced by OCSVM or SVDD is in agreement with the true density. Meanwhile, it can also reduce the integrated squared error （ISE）. Finally, experiments on several simulated datasets verify the revealed relationships.展开更多
In order to mine production and security information from security supervising data and to ensure security and safety involved in production and decision-making,a clustering analysis algorithm for security supervising...In order to mine production and security information from security supervising data and to ensure security and safety involved in production and decision-making,a clustering analysis algorithm for security supervising data based on a semantic description in coal mines is studied.First,the semantic and numerical-based hybrid description method of security supervising data in coal mines is described.Secondly,the similarity measurement method of semantic and numerical data are separately given and a weight-based hybrid similarity measurement method for the security supervising data based on a semantic description in coal mines is presented.Thirdly,taking the hybrid similarity measurement method as the distance criteria and using a grid methodology for reference,an improved CURE clustering algorithm based on the grid is presented.Finally,the simulation results of a security supervising data set in coal mines validate the efficiency of the algorithm.展开更多
This paper studied the application of minimum description length (MDL) criterion for estimating root-mean-squared (RMS) delay spread (RDS) for MIMO OFDM systems. The analytic relationship between the powers and the co...This paper studied the application of minimum description length (MDL) criterion for estimating root-mean-squared (RMS) delay spread (RDS) for MIMO OFDM systems. The analytic relationship between the powers and the correlation matrix of multipath components established the feasibility of the application of the MDL criterion to RDS estimation. The estimator presented both the estimate of instantaneous RDS and the estimates of noise variance, channel power and SNR of current channel with low computational complexity. Given the powers of the estimated multipath components, the MDL criterion was adopted to acquire the number of paths and the time delays of each path of current channel without making eigendecomposition of the correlation matrix normally required by MDL criterion, following which the noise variance and the power of each path can be estimated. The power delay profile (PDP) and RDS of the current channel were achieved. Simulation results showed that the proposed estimator was insensitive to variance of SNR and robust against frequency-selectivity.展开更多
The goal of this paper is to research one new characteristic of complex system. Brittleness, which is one new characteritic of complex system, is presented in this paper. The linguistic and qualitative descriptions of...The goal of this paper is to research one new characteristic of complex system. Brittleness, which is one new characteritic of complex system, is presented in this paper. The linguistic and qualitative descriptions of complex system are also given in this paper. Otherwise, the qualitative description of complex system is presented at first. On the basis of analyzing the existing brittleness problems, linguistic description and mathematic description of brittleness are given as well. Three kinds of phenomena to judge brittleness of complex system are also given, based on catastrophe theory. Basic characteristics of brittleness are given on the basis of its mathematic description. Two critical point sets are defined by using catastrophe theory. The definition of brittleness and its related theory can serve the control of complex system, and provide theoretical basis for the design and control of complex system.展开更多
An minimum description length(MDL) criterion is proposed to choose a good partition for a bipartite network. A heuristic algorithm based on combination theory is presented to approach the optimal partition. As the heu...An minimum description length(MDL) criterion is proposed to choose a good partition for a bipartite network. A heuristic algorithm based on combination theory is presented to approach the optimal partition. As the heuristic algorithm automatically searches for the number of partitions, no user intervention is required. Finally, experiments are conducted on various datasets, and the results show that our method generates higher quality results than the state-of-art methods, cross-association and bipartite, recursively induced modules. Experiment results also show the good scalability of the proposed algorithm. The method is applied to traditional Chinese medicine(TCM) formula and Chinese herbal network whose community structure is not well known, and found that it detects significant and it is informative community division.展开更多
基金Supported by the National Natural Science Foundation of China(60603029)the Natural Science Foundation of Jiangsu Province(BK2007074)the Natural Science Foundation for Colleges and Universities in Jiangsu Province(06KJB520132)~~
文摘One-class support vector machine （OCSVM） and support vector data description （SVDD） are two main domain-based one-class （kernel） classifiers. To reveal their relationship with density estimation in the case of the Gaussian kernel, OCSVM and SVDD are firstly unified into the framework of kernel density estimation, and the essential relationship between them is explicitly revealed. Then the result proves that the density estimation induced by OCSVM or SVDD is in agreement with the true density. Meanwhile, it can also reduce the integrated squared error （ISE）. Finally, experiments on several simulated datasets verify the revealed relationships.
基金The National Natural Science Foundation of China(No.50674086)Specialized Research Fund for the Doctoral Program of Higher Education(No.20060290508)the Postdoctoral Scientific Program of Jiangsu Province(No.0701045B)
文摘In order to mine production and security information from security supervising data and to ensure security and safety involved in production and decision-making,a clustering analysis algorithm for security supervising data based on a semantic description in coal mines is studied.First,the semantic and numerical-based hybrid description method of security supervising data in coal mines is described.Secondly,the similarity measurement method of semantic and numerical data are separately given and a weight-based hybrid similarity measurement method for the security supervising data based on a semantic description in coal mines is presented.Thirdly,taking the hybrid similarity measurement method as the distance criteria and using a grid methodology for reference,an improved CURE clustering algorithm based on the grid is presented.Finally,the simulation results of a security supervising data set in coal mines validate the efficiency of the algorithm.
文摘This paper studied the application of minimum description length (MDL) criterion for estimating root-mean-squared (RMS) delay spread (RDS) for MIMO OFDM systems. The analytic relationship between the powers and the correlation matrix of multipath components established the feasibility of the application of the MDL criterion to RDS estimation. The estimator presented both the estimate of instantaneous RDS and the estimates of noise variance, channel power and SNR of current channel with low computational complexity. Given the powers of the estimated multipath components, the MDL criterion was adopted to acquire the number of paths and the time delays of each path of current channel without making eigendecomposition of the correlation matrix normally required by MDL criterion, following which the noise variance and the power of each path can be estimated. The power delay profile (PDP) and RDS of the current channel were achieved. Simulation results showed that the proposed estimator was insensitive to variance of SNR and robust against frequency-selectivity.
基金Supported by the Commission of Science Technology and Industry for National Defense (J1600B001)
文摘The goal of this paper is to research one new characteristic of complex system. Brittleness, which is one new characteritic of complex system, is presented in this paper. The linguistic and qualitative descriptions of complex system are also given in this paper. Otherwise, the qualitative description of complex system is presented at first. On the basis of analyzing the existing brittleness problems, linguistic description and mathematic description of brittleness are given as well. Three kinds of phenomena to judge brittleness of complex system are also given, based on catastrophe theory. Basic characteristics of brittleness are given on the basis of its mathematic description. Two critical point sets are defined by using catastrophe theory. The definition of brittleness and its related theory can serve the control of complex system, and provide theoretical basis for the design and control of complex system.
基金Projects(61363037,31071700)supported by the National Natural Science Foundation of ChinaProject(2011GXNSFD018025)supported by the Natural Science Key Foundation of Guangxi Province,ChinaProject(KYTZ201108)supported by the Development Foundation of Chengdu University of Information Technology,China
文摘An minimum description length(MDL) criterion is proposed to choose a good partition for a bipartite network. A heuristic algorithm based on combination theory is presented to approach the optimal partition. As the heuristic algorithm automatically searches for the number of partitions, no user intervention is required. Finally, experiments are conducted on various datasets, and the results show that our method generates higher quality results than the state-of-art methods, cross-association and bipartite, recursively induced modules. Experiment results also show the good scalability of the proposed algorithm. The method is applied to traditional Chinese medicine(TCM) formula and Chinese herbal network whose community structure is not well known, and found that it detects significant and it is informative community division.
