In this paper, we propose a dimension reduction method of locality preserving projections based on QR-decomposition of training data matrix, namely LPP/QR. It is efficient and effective in under-sampled recognition of...
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In this paper, we propose a dimension reduction method of locality preserving projections based on QR-decomposition of training data matrix, namely LPP/QR. It is efficient and effective in under-sampled recognition of image and text data, especially when the number of dimension of data is greater than the number of training samples. Its theoretical foundation is presented. The equivalence between LPP/QR and generalized LPP is induced although LPP/QR is faster than generalized LPP. Several experiments are conducted on Yale face database. High recognition rates show that the algorithm performs better in under-sampled situations.
The theory of granule computing based on the quotient space is one of the three main granule computing theories. The emphasis is on the structure of the quotient space theory in this paper. Comparing with rough set th...
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The theory of granule computing based on the quotient space is one of the three main granule computing theories. The emphasis is on the structure of the quotient space theory in this paper. Comparing with rough set theory, the authors point out the importance of the structure in granule computing theory. A new method of constructing quotient space according to the structure is also presented in this paper. The differences between the quotient structure and structure-based method are proved. Finally, some examples show the rationality and feasibility of our methods.
A online infomax algorithm is proposed in this paper. The performances and properties of this online algorithm is investigated in detail. To the problem of the artifacts removal in real life EEG signal, both the onlin...
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Quotient space theory of problem solving, a formal model of granular computing, is generalized in the sense that topological structure is replaced by Cech's closure space. Some basic issues of granular computing, ...
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Quotient space theory of problem solving, a formal model of granular computing, is generalized in the sense that topological structure is replaced by Cech's closure space. Some basic issues of granular computing, such as the representation of real world at different levels of granularity, property preserving and the construction of granular world, are discussed in detail. It turns out that most of conclusions of the classical quotient space theory keep being valid, so intension and applicable fields are enriched and enlarged respectively.
Determination of the native state of a protein from its amino acid sequence is the goal of protein folding simulations, with potential applications in gene therapy and drug design. To predict a global minimum (GM) str...
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Determination of the native state of a protein from its amino acid sequence is the goal of protein folding simulations, with potential applications in gene therapy and drug design. To predict a global minimum (GM) structure of a given sequence is a difficult task. A genetic algorithm (GA) is an efficient approach to find lowest-energy conformation for HP lattice model. We have introduced some new operators (symmetric and cornerchange operators) to speed up the searching process and give the result more biology significance. The result shows these new operators improved the success of prediction, compared with standard GA for benchmark HP sequence up to 50 residues
World Wide Web has developed to an inherently distributed information system,which brings people great trouble in finding needed information although huge amount of information available on the *** search engine is a ...
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World Wide Web has developed to an inherently distributed information system,which brings people great trouble in finding needed information although huge amount of information available on the *** search engine is a very important tool for people to obtain information on the webs,but the low-precision and low-recall exist widely in current search *** effective and accurate intelligent search engine based on the expert systems technology has become the most important research *** paper analyzes the WWW with different granularities according to quotient space theory,gives summarization of search engine and describes an expert system built by Visual Prolog.
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.
The quotient space theory obtains a fusion model about semi-order structure under the condition of consistency information, harnessing topology relation among elements of the universe space and hierarchical structure....
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The quotient space theory obtains a fusion model about semi-order structure under the condition of consistency information, harnessing topology relation among elements of the universe space and hierarchical structure. It has great significance to forming a unified theory structure about information fusion technology. This paper gets a new semi-order structure fusion model under the condition of inconsistency information and proves incompleteness of its semi-order lattice . An example is presented in the paper at last as well as a new method is indicated for Bayesian network structure learning.
Let G be a graph and f: G→ G be a continuous map with at least one periodic point. Using the quote space method, the paper addresses that f is an equicontinuous map if and only if one of the following End(G)+2k+1 con...
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Let G be a graph and f: G→ G be a continuous map with at least one periodic point. Using the quote space method, the paper addresses that f is an equicontinuous map if and only if one of the following End(G)+2k+1 conditions holds: 1) {f jm(End(G)+2k)!}∞j=1 is uniformly convergent, in which m=1,2,…, End(G)+2k; and 2) There is a positive integer n esuring that {f jn}∞j=1 is uniformly convergent.
This paper concerns a greedy EM algorithm for t-mixture modeling, which is more robust than Gaussian mixture modeling when a typical points exist or the set of data has heavy tail. Local Kullback divergence is used to...
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This paper concerns a greedy EM algorithm for t-mixture modeling, which is more robust than Gaussian mixture modeling when a typical points exist or the set of data has heavy tail. Local Kullback divergence is used to determine how to insert new component. The greedy algorithm obviates the complicated initialization. The results are comparable to that of split-and-merge EM algorithm while the proposed algorithm is faster. Also the by product of a sequence of mixture models is useful for model selection. Experiments of synthetic data clustering and unsupervised color image segmentation are given.
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