Abstract:

For better signal processing and feature extracting of nonstationary signal, timefrequency analysis is one of the top interests and more and more research has been put on this topic. For the limitations of the conventional methods of timerequency analysis, a novel method of timefrequency analysis is analyzed which is applicable to nonstabilization and nonlinear signal. Empirical mode decomposition algorithm which is used to extract features of signals through utilizing the empirical mode decomposition and hilbert transformation are proposed and its characteristics are analyzed. The analysis method and steps of empirical mode decomposition timefrequency characteristic is presented. To demonstrate the validity and unique virtue of empirical mode decomposition timefrequency analysis method, the transient signal features abstraction and signal tendency abstraction are studied by the method. Simulation results have shown the feasibility and validity of the method. Lastly, timefrequency analytic method based on empirical mode decomposition is used to extract of signals trend component and to demonstrate the efficiency and superiority of this new timefrequency analytic method.

Key words: empirical mode decomposition, timefrequency analysis, characteristics parameters, transient signal