摘要
语音信号是一种典型的非平稳信号,其特性及表征本质特征的参数均是随时间变化的,而时频分析是分析时变谱的有力工具,Hilbert-Huang变换是一种新型的具有自适应性的时频分析方法,对于非线性、非平稳信号有清晰的物理意义,通过HHT变换,能够得到信号的时间-频率-振幅三维分布特征。分析了HHT算法的原理,采用了合适的端点效应处理方法提高了EMD的分解精度,通过仿真实验得到了语音信号更加精细的时频结构,并与STFT、WVD及Choi-Williams分布进行了对比,显示了HHT算法的优越性。
Speech signal is a typical non-stationary signal,its characteristic and feature parameters change along with time.Time-Frequency is a powerful tool for the analysis of time-varying spectrum.Hilbert-Huang Transform（HHT） is a new and self-adaptable method for time-frequency analysis.Its physical meaning is clear to nonlinear and non-stationary signal,it can get three dimensional distribution of time-frequency-amplitude.The theory of HHT is studied and the decomposition accuracy is improved by adopting the proper method to deal with end effect.Simulation experiments show that it can get finer time-frequency structure compared with STFT,WVD and Choi-Williams.
出处
《计算机工程与应用》
CSCD
北大核心
2010年第28期149-151,156,共4页
Computer Engineering and Applications
