变换和频谱分析
信号的频域表示揭示了难以在时域中分析的重要信号特征。通过频谱分析，您可以表征信号的频率成分。DSP System Toolbox™ 中的 FFT 和 IFFT System object 及模块支持将时域流信号转换为频域信号，反之亦然。要计算信号的频谱估计值，请使用 MATLAB® 中的 dsp.SpectrumEstimator System object™ 和 Simulink® 中的 Spectrum Estimator 模块。您可以使用频谱分析仪对象和模块来可视化频谱估计值。
DSP System Toolbox 中的频谱分析仪使用韦尔奇平均修正周期图方法和滤波器组方法。这两种方法都是基于 FFT 的频谱估计方法，它们对输入数据不做任何假设，可用于任何类型的信号。有关频谱分析仪使用的算法的详细信息，请参阅Spectral Analysis。要了解如何在 MATLAB 中估计流信号的功率谱密度，请参阅Estimate the Power Spectrum in MATLAB。
精选示例
Spectrum Analyzer Measurements
Use the Spectrum Analyzer block for harmonic distortion measurements (such as THD, SNR, SINAD, and SFDR), third-order intermodulation (TOI) distortion measurements, and adjacent channel power ratio (ACPR) measurements. The example also shows you how to view time-varying spectra by using a spectrogram and automatic peak detection. The example includes five amplifier models, with each model representing a typical setup to perform one of the measurements.
Zoom FFT
Showcases zoom FFT, which is a signal processing technique used to analyze a portion of a spectrum at a high resolution. DSP System Toolbox™ offers this functionality in MATLAB® through the dsp.ZoomFFT System object™, and in Simulink® through the Zoom FFT block in the DSP System Toolbox library.
Detect Air Compressor Sounds in Simulink Using Wavelet Scattering
Use the Wavelet Scattering block and a pretrained deep learning network to classify audio signals.
Detect Anomalies in ECG Data Using Wavelet Scattering and LSTM Autoencoder in Simulink
Use wavelet scattering and deep learning network to detect anomalies in ECG signals.
