Grey Information: Theory and Practical Applications (Advanced Information and Knowledge Processing)
Grey Information: Theory and Practical Applications (Advanced Information and Knowledge Processing)
Speech pitch determination based on Hilbert-Huang transform
Signal Processing
Grey system theory-based models in time series prediction
Expert Systems with Applications: An International Journal
Empirical mode decomposition for trivariate signals
IEEE Transactions on Signal Processing
A novel blind source separation method for single-channel signal
Signal Processing
PCSPA '10 Proceedings of the 2010 First International Conference on Pervasive Computing, Signal Processing and Applications
Adaptive time-frequency analysis based on autoregressive modeling
Signal Processing
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One of the open problems to which Hilbert-Huang transform (HHT) inevitably confront is end effect, a plague from which many data analysis methods have been suffering from the beginning. Aiming at mitigating end effects of HHT, a boundary extension method is introduced, which is based on the well-known gray prediction model termed as GM(1,1). Using the idea of cubic spline, the calculation of derivative to accumulated generating operation (AGO) series in GM(1,1) model is developed. We further make full use of residual series produced in the GM(1,1) model to achieve better prediction precision. According to numerical experiments on synthetic and real world signals, as well as comparisons of the proposed method with other six generally acknowledged methods, including the original HHT, multiple residual error gray model (MREM), ''window frame'', mirror extending (ME), autoregressive (AR) model, and artificial neural network (ANN) based HHT, it is demonstrated that our method significantly reduces end effects and improves decomposition and transformation results of HHT.