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Deep Learning with Simulink

Extend deep learning workflows using Simulink

Implement deep learning functionality in Simulink® models by using blocks from the Deep Neural Networks block library, included in the Deep Learning Toolbox™, or by using the Deep Learning Object Detector block from the Analysis & Enhancement block library included in the Computer Vision Toolbox™.

Deep learning functionality in Simulink uses MATLAB Function block that requires a supported compiler. For most platforms, a default C compiler is supplied with the MATLAB® installation. When using C++ language, you must install a compatible C++ compiler. To see a list of supported compilers, open Supported and Compatible Compilers, click the tab that corresponds to your operating system, find the Simulink Product Family table, and go to the For Model Referencing, Accelerator mode, Rapid Accelerator mode, and MATLAB Function blocks column. If you have multiple MATLAB-supported compilers installed on your system, you can change the default compiler using the mex -setup command. See Change Default Compiler.


Image ClassifierClassify data using a trained deep learning neural network (Seit R2020b)
PredictPredict responses using a trained deep learning neural network (Seit R2020b)
Stateful ClassifyClassify data using a trained deep learning recurrent neural network (Seit R2021a)
Stateful PredictPredict responses using a trained recurrent neural network (Seit R2021a)
Deep Learning Object DetectorDetect objects using trained deep learning object detector (Seit R2021b)




Reinforcement Learning

Code Generation