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 ...
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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 ...
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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...
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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.
This paper describes a preprocessing mask technique based statistical mixture components segmentation method for extracting blood vessels from brain magnetic resonance angiography (MRA) dataset. The voxels whose inten...
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ISBN:
(纸本)1581138849
This paper describes a preprocessing mask technique based statistical mixture components segmentation method for extracting blood vessels from brain magnetic resonance angiography (MRA) dataset. The voxels whose intensity is high in the dataset belong to blood vessels or brain skulls, which may bias the adjustment of the blood vessels. Maximum intensity projection (MIP) of the dataset in the Z axis direction was computed and segmented as a mask. The masked MRA dataset was segmented by a low threshold and the remanent voxels were modeled by one normal distribution and one uniform distribution. The parameters were estimated by Expectation-Maximization (EM) algorithm. The results show that this method is feasible for vessel extraction from MRA dataset.
In order to deal with some vague assertions more efficiently, fuzzy modal logics have been discussed by many researchers. This paper introduces the notation of fuzzy assertion based on propositional modal logic. As an...
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In order to deal with some vague assertions more efficiently, fuzzy modal logics have been discussed by many researchers. This paper introduces the notation of fuzzy assertion based on propositional modal logic. As an extension of the traditional semantics about the modal logics, the fuzzy Kripke semantics are considered and the formal system of the fuzzy reasoning based on propositional modal logic is established and the properties about the satisfiability of the reasoning system are discussed.
It is a vital and challenging issue in AI community to get the "Right Information" to the "Right People" in the "Right Language" in the "Right Timeframe" in the "Right Leve...
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ISBN:
(纸本)1577352017
It is a vital and challenging issue in AI community to get the "Right Information" to the "Right People" in the "Right Language" in the "Right Timeframe" in the "Right Level of Granularity". More and more researchers recognized that a well-designed instructional plan in intelligent tutoring systems will open up new possibilities of genuinely intelligent knowledge delivery for future education society. This paper proposes a novel three-layer student-state model and discusses the core elements in the architecture of a practical ITS model based on the theory of instructional automata The main advantages of instruction automata theory lie in that it can not only generate, regulate, update and implement instructional plans for individualized learner in the efficient and effective way, but also provide a uniform and extensible domain-independent environment for ITS designers and engineers.
An algebraic multi-class classification method AHSC, i.e. Algebraic Hyper Surface Classification, is proposed. The separating algebraic hyper surface of two-class data may be directly constructed by a single polynomia...
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ISBN:
(纸本)0780384032
An algebraic multi-class classification method AHSC, i.e. Algebraic Hyper Surface Classification, is proposed. The separating algebraic hyper surface of two-class data may be directly constructed by a single polynomial in theory, but it is too difficult to separate multi-class data by a single polynomial even though the polynomial is multivalued. AHSC can be used for classifying multi-class data by integrating a series of polynomial networks based on binary numbers which are used for lab.ling the classes of samples. The problem that multi-class data can not always be separated by a single polynomial is solved by AHSC. Moreover, the order of polynomial can be chosen by using an adaptive method. The experiment results show that the new method can efficiently and accurately classify multi-class and high dimension data.
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...
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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.
Verb classification is very important for temporal information analysis and semantic understanding. In English, this topic has been fully studied. However, there are few works and no systematic approaches in Chinese u...
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Verb classification is very important for temporal information analysis and semantic understanding. In English, this topic has been fully studied. However, there are few works and no systematic approaches in Chinese up to now. We propose a new approach using fuzzy sets and genetic algorithm for Chinese verb classification. Its contribution lies in two aspects: it (a) provides a flexible and systematic framework for solving this problem;and (b) achieves high precision in experiments.
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