异常检测
使用 AI 模型（包括深度学习网络）检测信号异常
提取稀疏时频特征来检测电磁、声学和振动数据中的异常。
函数
相关信息
精选示例
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.
Crack Identification from Accelerometer Data
Use wavelet and deep learning techniques to detect and localize transverse pavement cracks.
Detect Anomalies Using Wavelet Scattering with Autoencoders
Learn how to develop an alert system for predictive maintenance using wavelet scattering and deep learning.
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.
