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Dimensionality reduction is a very important part in the field of face recognition. In view of the problem of the traditional dimensionality reduction methods are inconvenient to select neighbor parameter K and the “dense” characteristic of the low-rank representation coefficient matrix. We presented a method that semi-supervised discriminant analysis via weighted low-rank representation and adaptive...
Industrial upgrading is a dynamic process that the industrial structure changes from a low level to a high level, thereby improving the economy. Firstly, in order to measure the development of industrial upgrading, this paper proposes four main quantitative indicators, which are the proportion of industrial structure, the degree of industrial growth, the direction of industrial upgrading, and the...
To remove the redundant features extracted by using 2DPCA methods, a face recognition method is presented based on 2DPCA and fuzzy-rough technique in this paper. The proposed method selects the important features for classification by using attribute reduction in fuzzy rough sets theory. The experimental results show the proposed method outperforms the face recognition methods based on 2DPCA.
The intelligent role in virtual environment can be located when using vision to get the target image, but there is a source separation problem in case of unknown complex natural signals. In order to resolve the source separation problem, this paper proposed the target three-dimensional modeling based on the visual image processing of virtual robot; applied the method based on the nonlinear Principle...
A new early warning method of the complex systems for real estate market is proposed in this paper. First, principle component analysis method is adopted, and 8 important indexes are screened from a great number of indices. Second, these 8 important indices are divided into 3 kinds which are called as antecedent, synchronous and delayed with the time-difference correlation analysis method. Third,...
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