Notice of Retraction End effects processing of Hilbert-Huang transform based on genetic algorithm and RBF Neural Network
作者： Jinghui Ma , Hong Jiang , Li Yao , Song Pu
DOI: 10.1109/ICCSIT.2010.5564604
关键词:
摘要: The problem of end effects in Hilbert-Huang transform is produced the Empirical Mode Decomposition (EMD), which has a badly effect on transform. In order to overcome this problem, multi-objective Genetic Algorithm (GA) for solving parameters selection RBF Neural Network (RBF_NN) (GRHHT) presented paper. Then RBF_NN used predict signal before EMD. scheme can effectively resolve effects. simulation results from typical definite signals demonstrate that Hilbert Huang could be resolved effectively, and its performance better than prediction methods by neural network support Vector Machine (SVM), respectively.
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