【摘要】 在介绍基于最大重叠离散小波包变换(Maximal Overlap Discrete Wavelet Packet Transform,简称MODWPT)的Hilbert谱方法的基础上,将基于MODWPT的Hilbert谱应用于非平稳信号的分析。采用MODWPT可将多分量的复杂信号分解为若干个瞬时频率和瞬时幅值都具有经典物理意义的分量之和,求出各个单分量信号的瞬时频率和瞬时幅值,再进行组合得到原始复杂信号完整的时频分布。对基于MODWPT和基于经验模态分解(Empirical Mode Decomposition,简称EMD)的Hilbert谱,在不同类型非平稳信号下的时频分析效果进行了比较和分析,结果表明了基于MODWPT的Hilbert谱分析方法的有效性。更多还原

【Abstract】 Maximal overlap discrete wavelet packet transform(MODWPT) is introduced and the Hilbert spectrum based on MODWPT is applied to non-stationary signal processing.MODWPT could decompose the complicated multi-component signal into a number of single components whose instantaneous frequency and instantaneous amplitude own physical meaning.Furthermore,the complete time-frequency distribution of complicated signal can be obtained after the instantaneous frequency and instantaneous amplitude of each single component are calculated.The analysis results from different kinds of non-stationary signals show that the Hilbert spectrum based on MODWPT could analysize non-stationary signals effectively and is superior to that based on empirical mode decomposition(EMD).更多还原