Simulink and Code Generation

Simulate machine learning models using Simulink and generate C/C++ code

Integrate machine learning models with system-level simulation and deploy them on edge devices. Simulate and test machine learning workflows using model-based design in Simulink®, and deploy them on embedded systems using Simulink Coder™. Generate C/C++ code using MATLAB® Coder to deploy Statistics and Machine Learning Toolbox™ functions on target devices that cannot run MATLAB.

Deployment Basics

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Featured Examples

Deploy Neural Network Regression Model to FPGA/ASIC Platform

Deploy Neural Network Regression Model to FPGA/ASIC Platform

Predict in Simulink using a neural network regression model, and deploy the Simulink model to an FPGA/ASIC platform by using HDL code generation.

Human Activity Recognition Simulink Model for Smartphone Deployment

Human Activity Recognition Simulink Model for Smartphone Deployment

Generate code from a classification Simulink model prepared for deployment to a smartphone.

Verify and Validate Machine Learning Models Using Model-Based Design

Verify and Validate Machine Learning Models Using Model-Based Design

Use Simulink to verify and validate machine learning models.

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In-Place Model Update of Offline Linear Model Using IncrementalClassificationLinear Predict Block

In-Place Model Update of Offline Linear Model Using IncrementalClassificationLinear Predict Block

Perform in-place model update without regenerating deployed code.