| 高阶时频变换理论、算法与应用 |
投稿时间：2021-01-22 修订日期：2021-02-20  点此下载全文 |
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| 中文摘要:非线性信号处理与特征提取是时频信号处理领域中的热点问题。传统时频分析方法受限于海森伯格不确定原则,在分析该类信号时存在较为严重的能量发散问题,导致分辨率不佳,无法为非线信号处理与特征提取提供精确的时频信息。为改善传统时频分析方法的能量聚集性,提升其时频分辨率,本文提出了一种高阶同步抽取变换算法,首先计算多个短时傅里叶变换,之后用以估计高阶瞬时频率算子,并结合短时傅里叶变换谱提取信号的非线性瞬时特征,从而能够为信号中的非线性特征提供高分辨率的时频谱。仿真分析验证了提出方法在时频特征刻画、能量聚集性以及抑噪方面的性能。实验分析验证了提出方法能够用于复杂多分量非线性信号处理,对于信号处理理论拓展具有重要意义。 |
| 中文关键词:时频分析 信号处理 瞬时频率估计 |
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| High-order time-frequency transform and its applications |
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| Abstract:Non-stationary signal processing is always a hot topic in the signal processing fields. Traditional time-frequency analysis methods are limited by the Heisenberg uncertainty principle, which cannot provide accurate time information for highly time-varying signals. In order to improve the energy concentration of the time-frequency analysis method, a high-order synchroextracting transform is proposed. By estimating the instantaneous frequency of the signal, the proposed method can characterize the non-stationary characteristics of complex signals. Simulation analysis and experimental analysis verify the performance of the proposed method in time-frequency feature characterization and noise suppression. |
| keywords:time-frequency analysis signal processing instantaneous frequency estimation |
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