A novel combined personalized feature framework is proposed for face recognition (FR). In the framework, the proposed linear discriminant analysis (LDA) makes use of the null space of the within-class scatter matrix e...A novel combined personalized feature framework is proposed for face recognition (FR). In the framework, the proposed linear discriminant analysis (LDA) makes use of the null space of the within-class scatter matrix effectively, and Global feature vectors (PCA-transformed) and local feature vectors (Gabor wavelet-transformed) are integrated by complex vectors as input feature of improved LDA. The proposed method is compared to other commonly used FR methods on two face databases (ORL and UMIST). Results demonstrated that the performance of the proposed method is superior to that of traditional FR ap- proaches展开更多
The main desire of this paper is to present several new interval oscillation criteria related to a generalized Riccati technique for certain second-order nonlinear differential equations.Our results extend some known ...The main desire of this paper is to present several new interval oscillation criteria related to a generalized Riccati technique for certain second-order nonlinear differential equations.Our results extend some known equations.Finally,several examples illustrate the effectiveness of our results.展开更多
Linear Discriminant Analysis （LDA） is one of the principal techniques used in face recognition systems. LDA is well-known scheme for feature extraction and dimension reduction. It provides improved performance over ...Linear Discriminant Analysis （LDA） is one of the principal techniques used in face recognition systems. LDA is well-known scheme for feature extraction and dimension reduction. It provides improved performance over the standard Principal Component Analysis （PCA） method of face recognition by introducing the concept of classes and distance between classes. This paper provides an overview of PCA, the various variants of LDA and their basic drawbacks. The paper also has proposed a development over classical LDA, i.e., LDA using wavelets transform approach that enhances performance as regards accuracy and time complexity. Experiments on ORL face database clearly demonstrate this and the graphical comparison of the algorithms clearly showcases the improved recognition rate in case of the proposed algorithm.展开更多
This is an introduction to antilinear operators. In following Wigner the terminus antilinear is used as it is standard in Physics.Mathematicians prefer to say conjugate linear. By restricting to finite-dimensional com...This is an introduction to antilinear operators. In following Wigner the terminus antilinear is used as it is standard in Physics.Mathematicians prefer to say conjugate linear. By restricting to finite-dimensional complex-linear spaces, the exposition becomes elementary in the functional analytic sense. Nevertheless it shows the amazing differences to the linear case. Basics of antilinearity is explained in sects. 2, 3, 4, 7 and in sect. 1.2: Spectrum, canonical Hermitian form, antilinear rank one and two operators,the Hermitian adjoint, classification of antilinear normal operators,(skew) conjugations, involutions, and acq-lines, the antilinear counterparts of 1-parameter operator groups. Applications include the representation of the Lagrangian Grassmannian by conjugations, its covering by acq-lines. As well as results on equivalence relations. After remembering elementary Tomita-Takesaki theory, antilinear maps, associated to a vector of a two-partite quantum system, are defined. By allowing to write modular objects as twisted products of pairs of them, they open some new ways to express EPR and teleportation tasks. The appendix presents a look onto the rich structure of antilinear operator spaces.展开更多
基金Project (No. 60275023) supported by the National Natural Sci-ence Foundation of China
文摘A novel combined personalized feature framework is proposed for face recognition (FR). In the framework, the proposed linear discriminant analysis (LDA) makes use of the null space of the within-class scatter matrix effectively, and Global feature vectors (PCA-transformed) and local feature vectors (Gabor wavelet-transformed) are integrated by complex vectors as input feature of improved LDA. The proposed method is compared to other commonly used FR methods on two face databases (ORL and UMIST). Results demonstrated that the performance of the proposed method is superior to that of traditional FR ap- proaches
基金Supported by Science Foundation for Young Teachers of Northeast Normal University（20080105） Supported by NSFC（10926105+2 种基金1100104110971022） Supported by SRFDP（200802001008）
文摘The main desire of this paper is to present several new interval oscillation criteria related to a generalized Riccati technique for certain second-order nonlinear differential equations.Our results extend some known equations.Finally,several examples illustrate the effectiveness of our results.
文摘Linear Discriminant Analysis （LDA） is one of the principal techniques used in face recognition systems. LDA is well-known scheme for feature extraction and dimension reduction. It provides improved performance over the standard Principal Component Analysis （PCA） method of face recognition by introducing the concept of classes and distance between classes. This paper provides an overview of PCA, the various variants of LDA and their basic drawbacks. The paper also has proposed a development over classical LDA, i.e., LDA using wavelets transform approach that enhances performance as regards accuracy and time complexity. Experiments on ORL face database clearly demonstrate this and the graphical comparison of the algorithms clearly showcases the improved recognition rate in case of the proposed algorithm.
文摘This is an introduction to antilinear operators. In following Wigner the terminus antilinear is used as it is standard in Physics.Mathematicians prefer to say conjugate linear. By restricting to finite-dimensional complex-linear spaces, the exposition becomes elementary in the functional analytic sense. Nevertheless it shows the amazing differences to the linear case. Basics of antilinearity is explained in sects. 2, 3, 4, 7 and in sect. 1.2: Spectrum, canonical Hermitian form, antilinear rank one and two operators,the Hermitian adjoint, classification of antilinear normal operators,(skew) conjugations, involutions, and acq-lines, the antilinear counterparts of 1-parameter operator groups. Applications include the representation of the Lagrangian Grassmannian by conjugations, its covering by acq-lines. As well as results on equivalence relations. After remembering elementary Tomita-Takesaki theory, antilinear maps, associated to a vector of a two-partite quantum system, are defined. By allowing to write modular objects as twisted products of pairs of them, they open some new ways to express EPR and teleportation tasks. The appendix presents a look onto the rich structure of antilinear operator spaces.
