Embedded AI Systems

Deploy deep learning into embedded targets and GPUs

Execute and deploy deep learning solutions on ARM®-based devices and embedded NVIDIA® GPUs. Generate code and use hardware to streamline signal segmentation, classification, and anomaly detection.

Related Information

Featured Examples

Deploy Signal Segmentation Deep Network on Raspberry Pi

Deploy Signal Segmentation Deep Network on Raspberry Pi

Generate a MEX function and a standalone executable to perform waveform segmentation on a Raspberry Pi®.

Modulation Classification Using Wavelet Analysis on NVIDIA Jetson

Modulation Classification Using Wavelet Analysis on NVIDIA Jetson

Use wavelets to classify waveforms on a NVIDIA Jetson®.

Classify ECG Signals Using DAG Network Deployed to FPGA

Classify ECG Signals Using DAG Network Deployed to FPGA

Classify human electrocardiogram (ECG) signals by deploying a trained directed acyclic graph (DAG) network.

New
Detect Air Compressor Sounds on a Raspberry Pi Using Wavelet Scattering and TensorFlow Lite Network

Detect Air Compressor Sounds on a Raspberry Pi Using Wavelet Scattering and TensorFlow Lite Network

Generate and deploy Raspberry Pi code to detect air compressor sounds using the Wavelet Scattering Simulink® block and a pretrained deep learning network.

(DSP System Toolbox)

  • Since R2025a
Deep Learning Code Generation on ARM for Fault Detection Using Wavelet Scattering and Recurrent Neural Networks

Deep Learning Code Generation on ARM for Fault Detection Using Wavelet Scattering and Recurrent Neural Networks

Perform acoustic-based fault detection on a Raspberry Pi using wavelet scattering and recurrent neural networks.

(Wavelet Toolbox)

  • Since R2023a
Deploy Signal Classifier on NVIDIA Jetson Using Wavelet Analysis and Deep Learning

Deploy Signal Classifier on NVIDIA Jetson Using Wavelet Analysis and Deep Learning

Generate and deploy a CUDA® executable to classify electrocardiogram signals using wavelet-derived features.

Deploy Signal Classifier Using Wavelets and Deep Learning on Raspberry Pi

Deploy Signal Classifier Using Wavelets and Deep Learning on Raspberry Pi

Classify human electrocardiogram signals on a Raspberry Pi using scalograms and a deep convolutional neural network.

Code Generation for a Deep Learning Simulink Model to Classify ECG Signals

Code Generation for a Deep Learning Simulink Model to Classify ECG Signals

Create and deploy a Simulink model for signal classification using wavelet-based features.

Real-Time Noise Detection on Raspberry Pi Using Deep Signal Anomaly Detector

Real-Time Noise Detection on Raspberry Pi Using Deep Signal Anomaly Detector

Detect the presence of noise on a Raspberry Pi device.