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Human capital is one of important factors to decide region economic increasing, which is influenced by various factors. Through Principal Component Analysis we can synthesize numerous indexes, eliminate information overlapping of the sample and reduce the input dimension of BP network. According to the nonlinear feature of human capital system, by using BP network altitudinal nonlinear map, we have...
A method of feature block two-dimensional principal component analysis (FB2DPCA) and multi-classifier combination is proposed for facial expression recognition. First, FB2DPCA is applied to extract human facial expression features, and then the expression classified result is obtained based on multi-classifier fusion with fuzzy integral. This proposed method is validated through the results of experiments...
This paper proposed an algorithm of feature selection used in fusion of soft computing and based on the chain of data-information-cognition. The algorithm is as follow: Firstly, the weights wij from input layer to hidden layer are obtained when the training accuracy of BP neural network (BPNN) is got. Where i denotes the i th feature and j denotes the j th node in hidden layer of BPNN. Secondly, zeta...
A method for the segmentation of synthetic aperture radar (SAR) image is presented in this paper. The method integrates the use of multi-scale technology, mixed-model information and support vector machines (SVM). First, the multi-scale autoregressive (MAR) model is modeled for multi-scale sequence of SAR image, and a multi-scale features, which is used as input of SVM, are extracted via the MAR model...
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