针对 ARM Cortex-M 处理器的 CMSIS 支持
Embedded Coder® Support Package for ARM Cortex-M Processors 支持针对函数、System object 和 Simulink® 模块的优化 C 代码生成。要生成此优化代码，您必须安装 Embedded Coder。
使用此支持包，您可以生成使用 CMSIS 库函数的 C 代码。您可以编译这些生成的代码，以提供在 ARM Cortex-M 处理器上运行的进行了优化的可执行文件。
还可以将生成的 ARM Cortex-M CRL 代码从 MATLAB® 移植到 KEIL μVision IDE 和 IAR Embedded Workbench。有关详细信息，请参阅将生成的 ARM Cortex-M CRL 代码从 MATLAB 移植到 KEIL μVision IDE 和将生成的 ARM Cortex-M CRL 代码从 MATLAB 移植到 IAR Embedded Workbench。
有关安装或更新支持包的信息，请参阅Install Support for Embedded Coder Support Package for ARM Cortex-M Processors。
主题
MATLAB 和 Simulink
- Supported Simulink Blocks with CMSIS Library for ARM Cortex-M Processors
Supported Simulink blocks with CMSIS library for ARM Cortex-M processors. - Supported MATLAB Functions with CMSIS Library for ARM Cortex-M Processors
Supported MATLAB functions with CMSIS functions for ARM Cortex-M processors.
DSP System Toolbox
- Supported DSP System Toolbox Blocks with CMSIS Library for ARM Cortex-M Processors
List of supported DSP System Toolbox™ blocks with CMSIS library for ARM Cortex-M processors. - Supported DSP System Toolbox System Objects with CMSIS Library for ARM Cortex-M Processors
List of supported DSP System Toolbox System objects with CMSIS library for ARM Cortex-M processors.
Deep Learning Toolbox
- Code Generation for Matrix Multiplication in Deep Learning Layers with CMSIS Library for ARM Cortex-M Processors
Learn the workflow to generate code for matrix multiplication operation in supported deep learning layers using the CMSIS library for ARM Cortex-M processors.
精选示例
Verify FIR Filter on ARM Cortex-M Processor
Use the code replacement library (CRL) for ARM® Cortex-M processors with DSP blocks. The model uses the FIR filter block to filter two sine waves of different frequencies.
Support Fixed-Point FIR Filter on ARM Cortex-M Processor
Use the code replacement library (CRL) for ARM® processors with DSP blocks. The model uses the fixed-point FIR filter block to filter two sine waves of different frequencies.
Support ARM CMSIS C Code Generation of dsp.FIRFilter in MATLAB Function Block
Use the code replacement library (CRL) for ARM® processors with DSP System object™. The model uses a MATLAB Function block that contains a dsp.FIRFilter System object to filter two sine waves of different frequencies.
Verify FIR Filter on ARM Cortex-M Processor in MATLAB
Use the code replacement library (CRL) for ARM® Cortex®-M processor with DSP System object™. The example uses a dsp.FIRFilter System object to filter two sine waves of different frequencies.
Parameteric Audio Equalizer for ARM Cortex-M Processor
Generate and run the optimized code of a parametric audio equalizer on ARM® Cortex®-M processor while adjusting equalizer response from within Simulink® environment. The optimized code uses CMSIS DSP library for the biquad filter in the equalizer.
Real-Time ECG QRS Detection on ARM Cortex-M Processor
Generate and run optimized code for real-time QRS detection of an electrocardiogram (ECG) signal on the ARM® Cortex®-M processor. It uses an ECG signal selector for choosing ECG signal sources with different mean heart rates in the Simulink® environment. The optimized code uses the CMSIS library for the discrete FIR blocks in the example.
Code Generation for Sound Classification on ARM Cortex-M Targets using CMSIS-NN
Use the CMSIS-NN library and pretrained network to generate code for the melSpectrogram (Audio Toolbox) example. In this example, you can classify white noise, brown noise and pink noise by generating a processor-in-the-loop (PIL) MEX function, which allows you to execute the generated code on target hardware, such as the STM32 Nucleo F767ZI board. The PIL interface in the MATLAB™ environment facilitates the execution of the generated executable on the target hardware.
Code Generation for Interpolated FIR Filter on ARM Cortex-M Target Using CMSIS
Generate and run optimized code using the ARM™ Cortex™-M CRL for an interpolated finite impulse response (IFIR) filter on the STM32F746G-Discovery hardware.
Deploy Parametric Audio Equalizer on ARM Cortex-M Processors
Deploy three-band parametric audio equalizer on the ARM™ Cortex™-M STM32F746G-Discovery board. You can deploy this parametric equalizer on any supported ARM Cortex-M hardware.
Code Generation and Deployment for Acoustic-Based Machine Fault Detection Using Deep Learning on ARM Cortex-M Hardware
Demonstrates code generation for acoustics-based machine fault recognition using a long-short-term-memory (LSTM) network and spectral descriptors. This example uses Embedded Coder™ with deep learning support to generate a "processor-in-the-loop" (PIL) executable function that leverages C code on ARM® Cortex-M hardware. The input data consists of acoustic time-series recordings from a faulty or healthy air compressors, and the output is the state of the mechanical machine predicted by the LSTM network. For details on audio preprocessing and network training, see the Acoustics-Based Machine Fault Recognition (Audio Toolbox).
Generate and Deploy Optimized Code for Digit Classification Deep Learning Network on ARM Cortex-M Target
Generate optimized code for a digit classification deep learning network and deploy the generated code on an ARM Cortex-M™ target. You create an image data set and load a pretrained digit classification deep learning network. Then, you create a digit classification Simulink® model using an Image Classifier block, which uses the pretrained network to classify the input image. Additionaly, you deploy the generated code to an ARM Cortex-M target and compare the performance of the generated code with and without the code replacement library (CRL).
