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AI for DSP

Wavelet scattering, deep signal anomaly detection

DSP System Toolbox™ provides features to model a wavelet scattering network and detect anomalies using deep learning network in Simulink®.

The Wavelet Scattering block creates a framework for wavelet time scattering in the Simulink environment. Use this block to derive low-variance features from real-valued data, and then use those features in machine learning and deep learning applications. For more information, see Wavelet Scattering (Wavelet Toolbox). The Wavelet Scattering block requires Wavelet Toolbox™.

The Deep Signal Anomaly Detector block detects real-time signal anomalies in Simulink using a trained long short-term memory (LSTM) autoencoder deep learning network model. You must first create and train a detector object in MATLAB® using the deepSignalAnomalyDetector function, and configure the block to use this model in Simulink. The Deep Signal Anomaly Detector block requires Deep Learning Toolbox™.


Wavelet ScatteringModel wavelet scattering network in Simulink (depuis R2022b)
Deep Signal Anomaly DetectorDetect signal anomalies using deep learning network in Simulink (depuis R2024a)