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Estimation of the blood Doppler frequency shift by a matching pursuit algorithm

机译:通过匹配追踪算法估算血液多普勒频移

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The diagnosis of arterial occlusive disease often depends on the Doppler spectrum analysis. We can normally use the short-time Fourier transform (STFT) to compute the time-frequency representation (TFR) of the Doppler blood flow signal. This method uses a fixed time-frequency window, making it inaccurate to analyze signals with relatively wide bandwidths that change rapidly with time. In order to estimate the Doppler frequency shift more accurately, even when the temporal flow velocity is rapid (high non-stationarity), we propose to use a modified version matching pursuit (MP) with stochastic dictionaries to estimate the time frequency representation of Doppler blood flow signals for extracting the mean frequency shift. Results show that the modified MP method can provide more accurate mean frequency waveforms than the STFT does.
机译:动脉闭塞性疾病的诊断通常取决于多普勒频谱分析。通常,我们可以使用短时傅立叶变换(STFT)计算多普勒血流信号的时频表示(TFR)。此方法使用固定的时频窗口,因此无法分析带宽相对较宽且随时间快速变化的信号。为了更准确地估计多普勒频移,即使在瞬时流速较快(非平稳性较高)时,我们建议使用带有随机字典的改进版本匹配追踪(MP)来估计多普勒血液的时频表示提取平均频移的流量信号。结果表明,改进的MP方法比STFT可以提供更准确的平均频率波形。

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