AI 在 DSP 中的应用
DSP System Toolbox™ 提供使用 Simulink® 中的深度学习网络提取信号统计量及检测信号异常的功能。
Time Feature Extractor 模块从信号中提取时域特征，如均值、RMS、标准差、SNR 和 SINAD。
Wavelet Scattering 模块创建了一个框架，用于在 Simulink 环境中实现小波时间散射。使用此模块从实数值数据中推导低方差特征，然后在机器学习和深度学习应用中使用这些特征。有关详细信息，请参阅Wavelet Scattering (Wavelet Toolbox)。Wavelet Scattering 模块需要 Wavelet Toolbox™。
Deep Signal Anomaly Detector 模块使用经过训练的长短期记忆 (LSTM) 自编码器深度学习网络模型来检测 Simulink 中的实时信号异常。您必须首先使用 deepSignalAnomalyDetector 函数在 MATLAB® 中创建和训练一个检测器对象，然后在 Simulink 中配置该模块以使用此模型。Deep Signal Anomaly Detector 模块需要 Deep Learning Toolbox™。
模块
主题
- Wavelet Scattering (Wavelet Toolbox)
Derive low-variance features from real-valued time series and image data.
- Fault Detection Using Wavelet Scattering and Recurrent Deep Networks (Wavelet Toolbox)
Classify faults in acoustic recordings of air compressors using a wavelet scattering network paired with a recurrent neural network. (自 R2021b 起)
精选示例
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 Air Compressor Sounds on a Raspberry Pi Using Wavelet Scattering and TensorFlow Lite Network
Generate and deploy Raspberry Pi® code to detect air compressor sounds using the Wavelet Scattering Simulink block and a pretrained deep learning network.
Fault Detection and Localization in Three-Phase Power Transmission Using Deep Signal Anomaly Detector in Simulink
Detect faults in three-phase power transmission using the Deep Signal Anomaly Detector block.
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.
Real-Time Noise Detection on Raspberry Pi Using Deep Signal Anomaly Detector
Detect the presence of noise on a Raspberry Pi device.
Deploy Air Compressor Fault Detection Using Wavelet Scattering and TensorFlow Lite on Desktops
Generate and deploy code to detect air compressor sounds using Wavelet Scattering and a TensorFlow Lite deep learning network.
