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Grey Wolf Optimizer (GWO) is a new meta-heuristic optimization. It is inspired by the unique predator strategy and organization system of grey wolves. Since the GWO algorithm is easy to fall into local optimum especially when it is used in the high-dimensional data, an improved GWO algorithm combined with Cuckoo Search (CS) is proposed in this paper. By introducing the global-search ability of CS...
In order to enhance efficiency and accuracy of dynamic hand gesture recognition based on HMM method. we propose a new HMM algorithm combined with the DTW for the computation's high complexity of HMM method in the training stage. The new HMM can establish the relationship of fuzzy closeness degree between the DTW algorithm and the HMM algorithm. Meanwhile, it can combine with the template adaptive...
The researches on feature selection play a very important role in the area of classification. In this paper, we introduce a heuristic wrapper method: Classification Contribution-Ratio Based Selection (CCRS). Using RBF neural network as a classifier, we did our experiments on a data set of 74 features extracted from 517 Chinese folk songs which come from 10 regions. The results show that Root Mean...
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