Signal prediction based on empirical mode decomposition and artificial neural networks

Signal prediction based on empirical mode decomposition and artificial neural networks

In view of the usefulness of Empirical Mode Decomposition (EMD), Artificial Neural Networks (ANN), and Most Relevant Matching Extension (MRME) methods in dealing with nonlinear signals, we propose a new way of combining these methods to deal with signal prediction. We found the results of combining...

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Bibliographic Details
Main Authors: Wang Yong, Liu Yanping, Yang Jing
Format: Article
Language:English
Published: KeAi Communications Co., Ltd. 2012-02-01
Series:Geodesy and Geodynamics
Subjects:
EMD (Empirical Mode Decomposition)
ANN (Artificial Neural Networks)
MRME (Most Relevant Matching Extension)
IMF (Intrinsic Mode Function)
endpoint problem
RBF (Radial Basis Function)
Online Access:http://www.sciencedirect.com/science/article/pii/S1674984715301099

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http://www.sciencedirect.com/science/article/pii/S1674984715301099

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