- Extracting relevant features from industrial vibration timeseries data using the Diagnostic Feature Designer app
- Setting up and training an LSTM-based autoencoder to detect abnormal behavior
- Evaluating the results on a validation dataset
Is there a way to create an LSTM Autoencoder for time-series data?
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is it possible to create an Autoencoder with the Deep Learning layers and LSTM layers and when yes how?
I have found mutliple refs. for python time-series autoencoders, but Matlab does not have the same layers, or am i missing something?
(I can´t use the trainAutoencoder(X) Function because the time-series don´t have the same length)
David Willingham on 4 May 2021
Here's an example of using LSTM based Autoencoders on our GitHub page: Industrial Machinery Anomaly Detection using an Autoencoder. This Predictive Maintenance example trains a deep learning autoencoder on normal operating data from an industrial machine. The example walks through: