A novel spatial interpolation method based on integrated radial basis function artificial neural networks （IRBFANNs） is proposed to provide accurate and stable predictions of heavy metals concentrations in soil at u...A novel spatial interpolation method based on integrated radial basis function artificial neural networks （IRBFANNs） is proposed to provide accurate and stable predictions of heavy metals concentrations in soil at un- sampled sites in a mountain region. The IRBFANNs hybridize the advantages of the artificial neural networks and the neural networks integration approach. Three experimental projects under different sampling densities are carried out to study the performance of the proposed IRBFANNs-based interpolation method. This novel method is compared with six peer spatial interpolation methods based on the root mean square error and visual evaluation of the distribution maps of Mn elements. The experimental results show that the proposed method performs better in accuracy and stability. Moreover, the proposed method can provide more details in the spatial distribution maps than the compared interpolation methods in the cases of sparse sampling density.展开更多
In the present paper, we calculate the Gaussian correction to the critical value J^c⊥ caused by quantum spin fluctuation in a two-dimensional spatially anisotropic Heisenberg antiferromagnet with integer spin S. Prev...In the present paper, we calculate the Gaussian correction to the critical value J^c⊥ caused by quantum spin fluctuation in a two-dimensional spatially anisotropic Heisenberg antiferromagnet with integer spin S. Previously, some authors computed this quantity by the mean-field theory based on the Sehwinger boson representation of spin operators. However, for S = 1, their result is much less than the one derived by numerical calculations. By taking the effect of quantum spin fluctuation into consideration, we are able to produce a greatly improved result.展开更多
We propose a novel method of slice image reconstruction with controllable spatial filtering by using the correlation of periodic delta-function arrays （PDFAs） with elemental images in computational integral imaging....We propose a novel method of slice image reconstruction with controllable spatial filtering by using the correlation of periodic delta-function arrays （PDFAs） with elemental images in computational integral imaging. The multiple PDFAs, whose spatial periods correspond to object＇s depths with the elemental image array （EIA）, can generate a set of spatially filtered EIAs for multiple object depths compared with the conventional method for the depth of a single object. We analyze a controllable spatial filtering effect by the proposed method. To show the feasibility of the proposed method, we carry out preliminary experiments for multiple objects and present the results.展开更多
基金The National Natural Science Foundation of China(No.61261007,61062005)the Key Program of Yunnan Natural Science Foundation(No.2013FA008)
文摘A novel spatial interpolation method based on integrated radial basis function artificial neural networks （IRBFANNs） is proposed to provide accurate and stable predictions of heavy metals concentrations in soil at un- sampled sites in a mountain region. The IRBFANNs hybridize the advantages of the artificial neural networks and the neural networks integration approach. Three experimental projects under different sampling densities are carried out to study the performance of the proposed IRBFANNs-based interpolation method. This novel method is compared with six peer spatial interpolation methods based on the root mean square error and visual evaluation of the distribution maps of Mn elements. The experimental results show that the proposed method performs better in accuracy and stability. Moreover, the proposed method can provide more details in the spatial distribution maps than the compared interpolation methods in the cases of sparse sampling density.
基金The project partially supported by National Natural Science Foundation of China under Grant No. 90403003 Numerical computation of this work was carried out on the Parallel Computer Cluster of Institute for Condensed Matter Physics （ICMP） at School of Physics, Peking University.
文摘In the present paper, we calculate the Gaussian correction to the critical value J^c⊥ caused by quantum spin fluctuation in a two-dimensional spatially anisotropic Heisenberg antiferromagnet with integer spin S. Previously, some authors computed this quantity by the mean-field theory based on the Sehwinger boson representation of spin operators. However, for S = 1, their result is much less than the one derived by numerical calculations. By taking the effect of quantum spin fluctuation into consideration, we are able to produce a greatly improved result.
基金supported by the information technology(IT)research and development program of MKE/KEIT(10041682Development of High-Definition 3D Image Processing Technologies Using Advanced Integral Imaging with Improved Depth Range)
文摘We propose a novel method of slice image reconstruction with controllable spatial filtering by using the correlation of periodic delta-function arrays （PDFAs） with elemental images in computational integral imaging. The multiple PDFAs, whose spatial periods correspond to object＇s depths with the elemental image array （EIA）, can generate a set of spatially filtered EIAs for multiple object depths compared with the conventional method for the depth of a single object. We analyze a controllable spatial filtering effect by the proposed method. To show the feasibility of the proposed method, we carry out preliminary experiments for multiple objects and present the results.
