saveModel
Description
saveModel(
creates a MAT-file in the current
directory containing the trained network and parameters corresponding to the signal anomaly
detector d
)d
. You can use the generated file with the Deep Signal
Anomaly Detector
Simulink® block. The generated file contains two variables:
detectorModel
— Adlnetwork
(Deep Learning Toolbox) object that stores the trained network corresponding tod
.detectorParameters
— A structure that contains the detection parameters used byd
, including the window length, the overlap length, and the threshold.
By default, the name of the generated file is the name of the detector with
Data
appended.
To load the trained network and detector parameters into the Deep Signal Anomaly Detector block, provide the path and file name of the generated MAT-file in the block dialog box.
Note
You must train the signal anomaly detector before calling
saveModel
.
Examples
Input Arguments
Version History
Introduced in R2024a
See Also
Objects
deepSignalAnomalyDetectorCNN
|deepSignalAnomalyDetectorLSTM
|deepSignalAnomalyDetectorLSTMForecaster
Functions
detect
|getModel
|plotAnomalies
|plotLoss
|plotLossDistribution
|resetState
|trainDetector
|updateDetector
Blocks
- Deep Signal Anomaly Detector (DSP System Toolbox)
Topics
- Detect Anomalies in ECG Data Using Wavelet Scattering and LSTM Autoencoder in Simulink (DSP System Toolbox)
- Detect Anomalies in Signals Using deepSignalAnomalyDetector
- Detect Anomalies in Machinery Using LSTM Autoencoder
- Anomaly Detection in Industrial Machinery Using Three-Axis Vibration Data (Predictive Maintenance Toolbox)