The theoiy of the quotient space is a new mathematical tool for the study of the different granularity *** uses a triple(X,f,T)to describe a problem,among which X stands for the domain of the problem,f stands for the ...
详细信息
The theoiy of the quotient space is a new mathematical tool for the study of the different granularity *** uses a triple(X,f,T)to describe a problem,among which X stands for the domain of the problem,f stands for the attribute of the domain,and T stands for the structure of the *** analysis and solution of the problem(X,f,T),along with the further analysis and study of the domain and its structure and attribute,help to the description of the different granularity world based upon the complete *** paper firstly introduces the theory of quotient space,and then focuses on the application of this theoiy through the granularity analysis of the searching in the WWW,which has successfully come to the definite result of different *** about the search engine also are presented.
Semi-G2 basis functions are introduced, the degree of which is larger than three. These basis functions are expressed explicitly via matrices decomposition. Based on them, equations for constructing G2 splines can be ...
详细信息
Semi-G2 basis functions are introduced, the degree of which is larger than three. These basis functions are expressed explicitly via matrices decomposition. Based on them, equations for constructing G2 splines can be presented independently of geometric shape parameters' values. It makes the equation's solving easier. Analysis shows that this method may be extended to be applicable for constructing Gn splines.
Independent component analysis (ICA) is a method for finding independent components from multivariate (multidimensional) statistical data. Based on the optimal estimation function, a method for the estimation of the s...
详细信息
Independent component analysis (ICA) is a method for finding independent components from multivariate (multidimensional) statistical data. Based on the optimal estimation function, a method for the estimation of the score function is developed. By using the Gaussian mixture model, an EM algorithm for approximating the probability density of the data is presented, and a stochastic gradient method is given to separate the independent components. To improve the accuracy and stability of the algorithm, an iterative method for estimating the PDF of data is presented, which can perform the separation of mixed sub-Gaussian from super-Gaussian sources. The performance of the method is shown by computer simulations.
Multivariate t-mixture modelling is more robust than Gaussian mixture modelling to a set of data containing a group or groups of observations with longer than Gaussian tails or a typical observations. To alleviate the...
详细信息
ISBN:
(纸本)0780384032
Multivariate t-mixture modelling is more robust than Gaussian mixture modelling to a set of data containing a group or groups of observations with longer than Gaussian tails or a typical observations. To alleviate the problem of local convergence of the traditional EM algorithm, a split-and-merge operation is introduced into the EM algorithm for multivariate t-mixtures. The split-and-merge equations are first presented theoretically and then a new merge method is acquired. Accordingly, a modified EM algorithm is constructed. Experiments of data clustering and unsupervised color image segmentation are given.
Panoramic mosaics methods based on 8-paramter planar homography matrix have to overcome the accumulated errors, when a sequence of images loops back on itself. Usual methods are computationally intensive, and can not ...
详细信息
ISBN:
(纸本)9628576623
Panoramic mosaics methods based on 8-paramter planar homography matrix have to overcome the accumulated errors, when a sequence of images loops back on itself. Usual methods are computationally intensive, and can not ensure complete consistency of homographies. This paper presents a simple method, which do not require the consistency of homographies. The method mainly exploits un-calibrated image perspective interpolation technique [1]. So it is of simple calculation and easy realization.
暂无评论