随着Internet上信息量的飞速增长,成千上万的网上文档需要分类以方便用户的浏览和获取。因此文档的自动分类工作已经越来越受到重视,一些相应的分类方法也应运而生。但其中很少有涉及到"层次化"的分类领域,且绝大多数方法仅...随着Internet上信息量的飞速增长,成千上万的网上文档需要分类以方便用户的浏览和获取。因此文档的自动分类工作已经越来越受到重视,一些相应的分类方法也应运而生。但其中很少有涉及到"层次化"的分类领域,且绝大多数方法仅仅返回单个分类结果。文中,我们提出了一种新的文档自动分类方法:MRHC(Multicategory ReturnedAlgorithmforHierarchicalClassification)。该方法着眼于层次化的分类技术,并在适当的情况下为文档返回多个分类结果。该方法中结合了特征削减和增量学习技术以便提高分类性能。最后,为了更加准确、客观的评价分类结果,提出了一种新的评估方法:LEP(Length of Error Path)。实验结果表明,提出的分类方法响应时间短,分类准确度高,具有较强的实用性。展开更多
In order to assess the climatical and ecological effect which returned the farmland to pasture or forest, the vegetation and crop in Northwest China with suitable threshold value were classified in this experiment by ...In order to assess the climatical and ecological effect which returned the farmland to pasture or forest, the vegetation and crop in Northwest China with suitable threshold value were classified in this experiment by using multi-temporal SPOT/VEGETATION dada and combing supervised classification with unsupervised classification. Compared with the data from Statistical Department and actual investigation, the precision of the classified result was above 85%.展开更多
In the multilevel thresholding segmentation of the image, the classification number is always given by the supervisor. To solve this problem, a fast multilevel thresholding algorithm considering both the threshold val...In the multilevel thresholding segmentation of the image, the classification number is always given by the supervisor. To solve this problem, a fast multilevel thresholding algorithm considering both the threshold value and the classification number is proposed based on the maximum entropy, and the self-adaptive criterion of the classification number is given. The algorithm can obtain thresholds and automatically decide the classification number. Experimental results show that the algorithm is effective.展开更多
[Objective] This study aimed to investigate the genetic diversity of agronomic traits and genetic relationships among core collections of bitter gourd.[Method] Total 141 germplasms of bitter gourd were selected,and th...[Objective] This study aimed to investigate the genetic diversity of agronomic traits and genetic relationships among core collections of bitter gourd.[Method] Total 141 germplasms of bitter gourd were selected,and the genetic diversity of 13 agronomic traits was analyzed.In addition,total 46 core collections of bitter gourd were employed,and their genetic relationships were analyzed based on the phenotypic values and genotypic values of 5 agronomic traits,respectively.[Result] The genetic diversity analysis of agronomic traits showed that the genetic diversity indexes of the 4 qualitative traits of bitter gourd germplasms ranged from 0.46 to 1.34;the distribution of the 9 quantitative traits data was more dispersed with average coefficient of variation of 20.02%.The genetic relationship analysis showed that based on the phenotypic values and genotypic values of the 5 quantitative traits,the genetic distances among the 46 core collections of bitter gourd were different.Based on the genotypic values,the genetic distances among the 46 bitter gourd core collections ranged from 0.84 to 10.71.The 46 germplasms were divided into 17 groups with the rescaled distance of 8.5,which further classified the relationships among different germplasms.[Conclusion] This study will lay a solid foundation for the effective utilization of core collections and new variety breeding in bitter gourd.展开更多
A new approach based on multiwavelets transformation and singular value decomposition (SVD) is proposed for the classification of image textures. Lower singular values are truncated based on its energy distribution to...A new approach based on multiwavelets transformation and singular value decomposition (SVD) is proposed for the classification of image textures. Lower singular values are truncated based on its energy distribution to classify the textures in the presence of additive white Gaussian noise (AWGN). The proposed approach extracts features such as energy, entropy, local homogeneity and max-min ratio from the selected singular values of multiwavelets transformation coefficients of image textures. The classification was carried out using probabilistic neural network (PNN). Performance of the proposed approach was compared with conventional wavelet domain gray level co-occurrence matrix (GLCM) based features, discrete multiwavelets transformation energy based approach, and HMM based approach. Experimental results showed the superiority of the proposed algorithms when compared with existing algorithms.展开更多
The problem caused by shortness or excessiveness of snapshots and by coherent sources in underwater acoustic positioning is considered.A matched field localization algorithm based on CS-MUSIC(Compressive Sensing Multi...The problem caused by shortness or excessiveness of snapshots and by coherent sources in underwater acoustic positioning is considered.A matched field localization algorithm based on CS-MUSIC(Compressive Sensing Multiple Signal Classification) is proposed based on the sparse mathematical model of the underwater positioning.The signal matrix is calculated through the SVD(Singular Value Decomposition) of the observation matrix.The observation matrix in the sparse mathematical model is replaced by the signal matrix,and a new concise sparse mathematical model is obtained,which means not only the scale of the localization problem but also the noise level is reduced;then the new sparse mathematical model is solved by the CS-MUSIC algorithm which is a combination of CS(Compressive Sensing) method and MUSIC(Multiple Signal Classification) method.The algorithm proposed in this paper can overcome effectively the difficulties caused by correlated sources and shortness of snapshots,and it can also reduce the time complexity and noise level of the localization problem by using the SVD of the observation matrix when the number of snapshots is large,which will be proved in this paper.展开更多
文摘随着Internet上信息量的飞速增长,成千上万的网上文档需要分类以方便用户的浏览和获取。因此文档的自动分类工作已经越来越受到重视,一些相应的分类方法也应运而生。但其中很少有涉及到"层次化"的分类领域,且绝大多数方法仅仅返回单个分类结果。文中,我们提出了一种新的文档自动分类方法:MRHC(Multicategory ReturnedAlgorithmforHierarchicalClassification)。该方法着眼于层次化的分类技术,并在适当的情况下为文档返回多个分类结果。该方法中结合了特征削减和增量学习技术以便提高分类性能。最后,为了更加准确、客观的评价分类结果,提出了一种新的评估方法:LEP(Length of Error Path)。实验结果表明,提出的分类方法响应时间短,分类准确度高,具有较强的实用性。
基金Supported by the National Natural Science Foundation of China(No.40675071)~~
文摘In order to assess the climatical and ecological effect which returned the farmland to pasture or forest, the vegetation and crop in Northwest China with suitable threshold value were classified in this experiment by using multi-temporal SPOT/VEGETATION dada and combing supervised classification with unsupervised classification. Compared with the data from Statistical Department and actual investigation, the precision of the classified result was above 85%.
文摘In the multilevel thresholding segmentation of the image, the classification number is always given by the supervisor. To solve this problem, a fast multilevel thresholding algorithm considering both the threshold value and the classification number is proposed based on the maximum entropy, and the self-adaptive criterion of the classification number is given. The algorithm can obtain thresholds and automatically decide the classification number. Experimental results show that the algorithm is effective.
文摘[Objective] This study aimed to investigate the genetic diversity of agronomic traits and genetic relationships among core collections of bitter gourd.[Method] Total 141 germplasms of bitter gourd were selected,and the genetic diversity of 13 agronomic traits was analyzed.In addition,total 46 core collections of bitter gourd were employed,and their genetic relationships were analyzed based on the phenotypic values and genotypic values of 5 agronomic traits,respectively.[Result] The genetic diversity analysis of agronomic traits showed that the genetic diversity indexes of the 4 qualitative traits of bitter gourd germplasms ranged from 0.46 to 1.34;the distribution of the 9 quantitative traits data was more dispersed with average coefficient of variation of 20.02%.The genetic relationship analysis showed that based on the phenotypic values and genotypic values of the 5 quantitative traits,the genetic distances among the 46 core collections of bitter gourd were different.Based on the genotypic values,the genetic distances among the 46 bitter gourd core collections ranged from 0.84 to 10.71.The 46 germplasms were divided into 17 groups with the rescaled distance of 8.5,which further classified the relationships among different germplasms.[Conclusion] This study will lay a solid foundation for the effective utilization of core collections and new variety breeding in bitter gourd.
文摘A new approach based on multiwavelets transformation and singular value decomposition (SVD) is proposed for the classification of image textures. Lower singular values are truncated based on its energy distribution to classify the textures in the presence of additive white Gaussian noise (AWGN). The proposed approach extracts features such as energy, entropy, local homogeneity and max-min ratio from the selected singular values of multiwavelets transformation coefficients of image textures. The classification was carried out using probabilistic neural network (PNN). Performance of the proposed approach was compared with conventional wavelet domain gray level co-occurrence matrix (GLCM) based features, discrete multiwavelets transformation energy based approach, and HMM based approach. Experimental results showed the superiority of the proposed algorithms when compared with existing algorithms.
基金supported by the National Natural Science Foundation of China (61202208)
文摘The problem caused by shortness or excessiveness of snapshots and by coherent sources in underwater acoustic positioning is considered.A matched field localization algorithm based on CS-MUSIC(Compressive Sensing Multiple Signal Classification) is proposed based on the sparse mathematical model of the underwater positioning.The signal matrix is calculated through the SVD(Singular Value Decomposition) of the observation matrix.The observation matrix in the sparse mathematical model is replaced by the signal matrix,and a new concise sparse mathematical model is obtained,which means not only the scale of the localization problem but also the noise level is reduced;then the new sparse mathematical model is solved by the CS-MUSIC algorithm which is a combination of CS(Compressive Sensing) method and MUSIC(Multiple Signal Classification) method.The algorithm proposed in this paper can overcome effectively the difficulties caused by correlated sources and shortness of snapshots,and it can also reduce the time complexity and noise level of the localization problem by using the SVD of the observation matrix when the number of snapshots is large,which will be proved in this paper.
