EMD-HHT Algorithm Developed by National Central University in Taiwan

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The EMD-HHT algorithm was developed by National Central University in Taiwan, with the director of the research center serving as its founding creator. The algorithm integrates Empirical Mode Decomposition (EMD) and Hilbert–Huang Transform (HHT) for advanced time-frequency signal analysis.

Detailed Documentation

The EMD-HHT algorithm developed by National Central University in Taiwan has widespread applications in the field of signal processing. Created under the leadership of the center's director as its founding researcher, the algorithm combines Empirical Mode Decomposition (EMD) and Hilbert–Huang Transform (HHT) to extract time-frequency characteristics from signals. This method holds significant importance in areas such as signal processing, vibration analysis, and image processing. By employing the EMD-HHT algorithm, researchers can analyze spectral characteristics of signals more accurately and conduct in-depth investigations into their time-frequency behavior. In practical implementations, the EMD algorithm first decomposes a signal into intrinsic mode functions (IMFs), followed by HHT applying the Hilbert transform to each IMF to obtain instantaneous frequency data—enabling high-resolution time-frequency representations suitable for non-stationary signal analysis.

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