generateSimulink

Class: Autoencoder

(To be removed) Generate a Simulink model for the autoencoder

generateSimulink will be removed in a future release. For more information, see Transition Legacy Neural Network Code to dlnetwork Workflows.

For advice on updating your code, see Version History.

Syntax

generateSimulink(autoenc)

Description

generateSimulink(autoenc) creates a Simulink^® model for the autoencoder, autoenc.

Input Arguments

autoenc — Trained autoencoder

Autoencoder object

Trained autoencoder, specified as an Autoencoder object.

Examples

Generate Simulink Model for Autoencoder

Load the training data.

X = digitSmallCellArrayData;

The training data is a 1-by-500 cell array, where each cell containing a 28-by-28 matrix representing a synthetic image of a handwritten digit.

Train an autoencoder with a hidden layer containing 25 neurons.

hiddenSize = 25;
autoenc = trainAutoencoder(X,hiddenSize,...
        'L2WeightRegularization',0.004,...
        'SparsityRegularization',4,...
        'SparsityProportion',0.15);

Create a Simulink model for the autoencoder, autoenc.

generateSimulink(autoenc)

Version History

Introduced in R2015b

R2026a: generateSimulink will be removed

generateSimulink will be removed in a future release.

To learn more about autoencoder workflows, see these examples and topics:

• Build Networks with Deep Network Designer

• Time Series Anomaly Detection Using Deep Learning

• Detect Anomalies Using Wavelet Scattering with Autoencoders

• Train Variational Autoencoder (VAE) to Generate Images

• List of Deep Learning Layer Blocks and Subsystems

• Code Generation for Deep Learning Networks

For more information, see Transition Legacy Neural Network Code to dlnetwork Workflows.