时频分析 -凯发k8网页登录
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
信号分析器 | 可视化和比较多个信号和频谱 |
label signal attributes, regions, and points of interest, and extract features |
函数
主题
时频估计
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.
显示线性 fm 信号的频谱图和持久频谱。
compute the instantaneous frequency of a signal using 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
- (wavelet toolbox)
perform and interpret time-frequency analysis of signals using the continuous wavelet transform. - (radar toolbox)
classify pedestrians and bicyclists based on their micro-doppler characteristics using deep learning and time-frequency analysis. - (phased array system toolbox)
classify radar and communications waveforms using the wigner-ville distribution (wvd) and a deep convolutional neural network (cnn).