A novel supervised dimensionality reduction algorithm, named discriminant embedding by sparse representation and nonparametric discriminant analysis(DESN), was proposed for face recognition. Within the framework of DE...A novel supervised dimensionality reduction algorithm, named discriminant embedding by sparse representation and nonparametric discriminant analysis(DESN), was proposed for face recognition. Within the framework of DESN, the sparse local scatter and multi-class nonparametric between-class scatter were exploited for within-class compactness and between-class separability description, respectively. These descriptions, inspired by sparse representation theory and nonparametric technique, are more discriminative in dealing with complex-distributed data. Furthermore, DESN seeks for the optimal projection matrix by simultaneously maximizing the nonparametric between-class scatter and minimizing the sparse local scatter. The use of Fisher discriminant analysis further boosts the discriminating power of DESN. The proposed DESN was applied to data visualization and face recognition tasks, and was tested extensively on the Wine, ORL, Yale and Extended Yale B databases. Experimental results show that DESN is helpful to visualize the structure of high-dimensional data sets, and the average face recognition rate of DESN is about 9.4%, higher than that of other algorithms.展开更多
Many analytical methods have been adopted to estimate the slope stability by providing various stability numbers,e.g.static safety of factor(static FoS)or the critical seismic acceleration coefficient,while little att...Many analytical methods have been adopted to estimate the slope stability by providing various stability numbers,e.g.static safety of factor(static FoS)or the critical seismic acceleration coefficient,while little attention has been given to the relationship between the slope stability numbers and the critical seismic acceleration coefficient.This study aims to investigate the relationship between the static FoS and the critical seismic acceleration coefficient of soil slopes in the framework of the upper-bound limit analysis.Based on the 3D rotational failure mechanism,the critical seismic acceleration coefficient using the pseudo-static method and the static FoS using the strength reduction technique are first determined.Then,the relationship between the static FoS and the critical seismic acceleration coefficient is presented under considering the slope angleβ,the frictional angleφ,and the dimensionless coefficients B/H and c/γH.Finally,a fitting formula between the static FoS and the critical seismic acceleration coefficient is proposed and validated by analytical and numerical results.展开更多
基金Project(40901216)supported by the National Natural Science Foundation of China
文摘A novel supervised dimensionality reduction algorithm, named discriminant embedding by sparse representation and nonparametric discriminant analysis(DESN), was proposed for face recognition. Within the framework of DESN, the sparse local scatter and multi-class nonparametric between-class scatter were exploited for within-class compactness and between-class separability description, respectively. These descriptions, inspired by sparse representation theory and nonparametric technique, are more discriminative in dealing with complex-distributed data. Furthermore, DESN seeks for the optimal projection matrix by simultaneously maximizing the nonparametric between-class scatter and minimizing the sparse local scatter. The use of Fisher discriminant analysis further boosts the discriminating power of DESN. The proposed DESN was applied to data visualization and face recognition tasks, and was tested extensively on the Wine, ORL, Yale and Extended Yale B databases. Experimental results show that DESN is helpful to visualize the structure of high-dimensional data sets, and the average face recognition rate of DESN is about 9.4%, higher than that of other algorithms.
基金Project(2017YFB1201204)supported by the National Key R&D Program of ChinaProject(1053320190957)supported by the Fundamental Research Funds for the Central Universities,China。
文摘Many analytical methods have been adopted to estimate the slope stability by providing various stability numbers,e.g.static safety of factor(static FoS)or the critical seismic acceleration coefficient,while little attention has been given to the relationship between the slope stability numbers and the critical seismic acceleration coefficient.This study aims to investigate the relationship between the static FoS and the critical seismic acceleration coefficient of soil slopes in the framework of the upper-bound limit analysis.Based on the 3D rotational failure mechanism,the critical seismic acceleration coefficient using the pseudo-static method and the static FoS using the strength reduction technique are first determined.Then,the relationship between the static FoS and the critical seismic acceleration coefficient is presented under considering the slope angleβ,the frictional angleφ,and the dimensionless coefficients B/H and c/γH.Finally,a fitting formula between the static FoS and the critical seismic acceleration coefficient is proposed and validated by analytical and numerical results.
