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For adaptively analyzing non-stationary and nonlinear signals, Hilbert-Huang Transform (HHT) has recently been pioneered by Huang et al. In this paper, new stock prices of the prediction model is presented by combining the Hilbert-Huang transform. Intrinsic Mode Functions in the low frequency parts are obtained to replace the traditional motive average lines to analyze stock prices. The simulation...
The key feature of Empirical Mode Decomposition (EMD) is to decompose a signal into so-called intrinsic mode functions (IMFs). Furthermore, the Hilbert spectral analysis of IMFs provides frequency information evolving with time and quantifies the amount of variation due to oscillations at different time scales and locations. In general most of the Bio-medical signals such as electrocardiogram (ECG),...
Empirical Mode Decomposition (EMD) is an effective, non-linear and non-stationary data analysis method, which can decompose the original signal into several intrinsic mode functions(IMFs). However the frequency resolution of EMD has not been thoroughly investigated so far. In this paper a signal which contains two different frequency components was do composed with EMD, and subsequently the obtained...
At present, most of the studies on the relationship between El Nino Southern Oscillation and agricultural futures focus on perceptual and directly data analysis. This article uses EMD algorithm on endpoints processed data to decompose wheat futures price into seven Intrinsic Mode Function and one Residue. Then do symbolic clustering combined with SSVS method and denoised ENSO index. The results not...
Spectral analysis of heart rate variability (HRV) is used for the assessment of cardiovascular autonomic control. In this study data driven adaptive technique empirical mode decomposition (EMD) and the associated Hilbert spectrum has been used to evaluate the effect of local anesthesia on HRV parameters in a group of fourteen patients undergoing brachial plexus block (local anesthesia) using transarterial...
The newly developed Hilbert-Huang transform (HHT) is introduced briefly in this paper. The HHT method is specially developed for analyzing nonlinear and non-stationary data. The method consists of two parts: (1) the empirical mode decomposition (EMD), and (2) the Hilbert spectral analysis. The EMD, which is the first part of the theory, can decompose any complicated data set into a finite and often...
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