CMSIS Support for ARM Cortex-M Processors

Generate optimized code to run on the ARM® Cortex®-M processors

The Embedded Coder® Support Package for ARM Cortex-M Processors supports optimized C code generation for functions, System objects, and Simulink® blocks. To generate this optimized code, you must install Embedded Coder.

Using this support package, you can generate C code that uses the CMSIS library functions. You can compile this generated code to provide optimized executables that run on ARM Cortex-M processors.

You can also port the generated ARM Cortex-M CRL code from MATLAB® to KEIL μVision IDE and IAR Embedded Workbench. For details, see Port the Generated ARM Cortex-M CRL Code from MATLAB to KEIL μVision IDE and Port the Generated ARM Cortex-M CRL Code from MATLAB to IAR Embedded Workbench.

For information about installing or updating the support package, see Install Support for Embedded Coder Support Package for ARM Cortex-M Processors.

Topics

MATLAB and Simulink

DSP System Toolbox

Deep Learning Toolbox

Featured Examples

Verify FIR Filter on ARM Cortex-M Processor

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

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

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

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

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

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

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 Classify Sound Using Deep Learning 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

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 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

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 example.

New
Generate and Deploy Optimized Code for Digit Classification Deep Learning Network on ARM Cortex-M Target

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).