Simulink 和代码生成

使用 Simulink 进行机器学习模型仿真并生成 C/C++ 代码

将机器学习模型与系统级仿真进行集成并将其部署在边缘设备上。在 Simulink® 中使用基于模型的设计对机器学习工作流进行仿真和测试，并使用 Simulink Coder™ 将它们部署在嵌入式系统上。使用 MATLAB® Coder 生成 C/C++ 代码，以在无法运行 MATLAB 的目标设备上部署 Statistics and Machine Learning Toolbox™ 函数。

部署基础知识

类别

精选示例

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.

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.