Anomaly Detection

Anomaly Detection Using Convolutional Autoencoder with Wavelet Scattering Sequences

Detect anomalies in acoustic data using wavelet scattering and the deepSignalAnomalyDetector object.

Detect Anomalies in Signals Using deepSignalAnomalyDetector

Use autoencoders to detect abnormal points or segments in time-series data.

Detect Anomalies in Machinery Using LSTM Autoencoder

Use a long short-term memory autoencoder to detect anomalies in data from an industrial machine.

Anomaly Detection Using Autoencoder and Wavelets

Use wavelet-extracted features and an autoencoder to detect arc signals in a DC system.

Crack Identification from Accelerometer Data

Use wavelet and deep learning techniques to detect and localize transverse pavement cracks.

(Deep Learning Toolbox)

Detect Anomalies Using Wavelet Scattering with Autoencoders

Learn how to develop an alert system for predictive maintenance using wavelet scattering and deep learning.

(Deep Learning Toolbox)

Fault Detection Using Wavelet Scattering and Recurrent Deep Networks

Classify faults in acoustic recordings of air compressors using a wavelet scattering network paired with a recurrent neural network.

(Deep Learning Toolbox)