摘要
针对Cohen类二次型时频分布存在的交叉项,提出一种基于EMD与Choi-Williams分布相结合的方法,利用经验模态分解将信号从频域上分离若干个固有模态函数经过去伪后进行Cohen分布的时频变换,将得到的结果叠加重构出原始信号的Cohen类时频分布.仿真结果表明,该方法能有效抑制时频分布的交叉项,保证Cohen分布的时频聚集性,提取扰动特征.
In order to suppress the cross term interference in the Cohen-class quadratic time-frequency dis- tribution, a method was proposed based on empirical mode decomposition （EMD） and Choi-Williams dis- tribution. In this method, several intrinsic mode functions （IMFs） of the signals were separated from the frequency domain by using EMD. The time-frequency transformation of Cohen-class distribution was car- ried out after deleting the false components generated by EMD, and then the Cohen-class time-frequency distribution of original signal was reconstructed by means of linear superposition of the IMl^s Cohen-class distribution results. Simulation results showed that the method could be used to suppress effectively the cross terms of Cohen-class distribution, ensure Cohen-class distribution time-frequency concentration, and extract disturbance features.
出处
《兰州理工大学学报》
CAS
北大核心
2012年第6期78-81,共4页
Journal of Lanzhou University of Technology
基金
国家自然科学基金(61101161)
