时频分析
频谱图、同步压缩、重排、Wigner-Ville、时频边缘、数据自适应方法
Signal Processing Toolbox™ 提供的函数和 App 可用于可视化和比较非平稳信号的时频内容。计算短时傅里叶变换及其逆变换。使用重排或傅里叶同步压缩获得清晰的频谱估计。绘制交叉频谱图、Wigner-Ville 分布和持久频谱。提取并跟踪时频脊。估计瞬时频率、瞬时带宽、谱峭度和谱熵。使用经验或变分模态分解和 Hilbert-Huang 变换执行数据自适应时频分析。
App
函数
主题
时频估计
- Spectrogram Computation with Signal Processing Toolbox
Compute and display spectrograms of signals using Signal Processing Toolbox functions. - Time-Frequency Gallery
Examine the features and limitations of the time-frequency analysis functions provided by Signal Processing Toolbox. - 基于 FFT 的时频分析
显示线性 FM 信号的频谱图和持久频谱。 - Instantaneous Frequency of Complex Chirp
Compute the instantaneous frequency of a signal using the Fourier synchrosqueezed transform. - Detect Closely Spaced Sinusoids with the Fourier Synchrosqueezed Transform
Determine how separate in frequency two sinusoids must be for the Fourier synchrosqueezed transform to resolve them.
时频应用
- Practical Introduction to Time-Frequency Analysis Using the Continuous Wavelet Transform (Wavelet Toolbox)
Perform and interpret time-frequency analysis of signals using the continuous wavelet transform. - Pedestrian and Bicyclist Classification Using Deep Learning (Radar Toolbox)
Classify pedestrians and bicyclists based on their micro-Doppler characteristics using deep learning and time-frequency analysis. - Radar and Communications Waveform Classification Using Deep Learning (Phased Array System Toolbox)
Classify radar and communications waveforms using the Wigner-Ville distribution (WVD) and a deep convolutional neural network (CNN).