摘要
根据研究可知,当疾病或者其他情况使得血管发生病变时,血流信号所包含的信息在靠近血管壁的位置会发生明显的变化。对超声多普勒血流信号进行频谱的分析具有非常重要的意义,因为,血流信号的变化可以由其时频分布谱体现出来。在本论文中,分别利用传统的STFT算法和基于随机字典的Matching Pursuit算法(MP算法)对同一血流信号的时频分布谱、平均频率曲线及最大频率曲线进行分析。结果表明:基于随机字典的Matching Pursuit算法和传统的STFT算法进行比较时,其估计出的时频分布谱以及从谱中提取出的曲线都是更加准确和精确的。
The result of research shows that,when blood vessels become narrow or hardened because of disease or other conditions,the blood flow near the wall of the vessel changes significantly.The change of blood flow has a close relationship with the time-frequency distribution.In this study,use the STFT and the MP algorithm to calculate the same blood signal,and analyse it＇s TFR（time-frequency distribution）,mean frequency and maximum frequency waveforms.It is shown that,the MP algorithm can estimated more accurate and exact spectrum and waveforms than STFT algorithm.
出处
《电子技术（上海）》
2017年第9期17-20,共4页
Electronic Technology
