Embedded AI Systems
Execute and deploy deep learning solutions on hardware.
Functions
Signal Processing Layers
cwtLayer | Continuous wavelet transform layer (Since R2022b) |
icwtLayer | Inverse continuous wavelet transform layer (Since R2024b) |
modwtLayer | Maximal overlap discrete wavelet transform layer (Since R2022b) |
stftLayer | Short-time Fourier transform layer (Since R2021b) |
istftLayer | Inverse short-time Fourier transform layer (Since R2024a) |
Feature Extraction
dlcwt | Deep learning continuous wavelet transform (Since R2022b) |
dlicwt | Deep learning inverse continuous 1-D wavelet transform (Since R2024b) |
dlmodwt | Deep learning maximal overlap discrete wavelet transform and multiresolution analysis (Since R2022a) |
dlstft | Deep learning short-time Fourier transform (Since R2021a) |
dlistft | Deep learning inverse short-time Fourier transform (Since R2024a) |
cwtfilterbank | Continuous wavelet transform filter bank |
findchangepts | Find abrupt changes in signal |
findpeaks | Find local maxima |
modwt | Maximal overlap discrete wavelet transform |
risetime | Rise time of positive-going bilevel waveform transitions |
stft | Short-time Fourier transform |
signalFrequencyFeatureExtractor | Streamline signal frequency feature extraction (Since R2021b) |
signalTimeFeatureExtractor | Streamline signal time feature extraction (Since R2021a) |
signalTimeFrequencyFeatureExtractor | Streamline signal time-frequency feature extraction (Since R2024a) |
waveletScattering | Wavelet time scattering |
Topics
- Deep Learning Code Generation on ARM for Fault Detection Using Wavelet Scattering and Recurrent Neural Networks (Wavelet Toolbox)
Perform acoustic-based fault detection on a Raspberry Pi® using wavelet scattering and recurrent neural networks. (Since R2023a)
Featured Examples
Wireless Resource Allocation Using Graph Neural Network
Use graph neural networks for power allocation in wireless networks.
Modulation Classification Using Wavelet Analysis on NVIDIA Jetson
Use wavelets to classify waveforms on a NVIDIA Jetson®.
Deploy Signal Segmentation Deep Network on Raspberry Pi
Generate a MEX function and a standalone executable to perform waveform segmentation on a Raspberry Pi.
Classify ECG Signals Using DAG Network Deployed to FPGA
Classify human electrocardiogram (ECG) signals by deploying a trained directed acyclic graph (DAG) network.
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.
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.
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.
Real-Time Noise Detection on Raspberry Pi Using Deep Signal Anomaly Detector
Detect the presence of noise on a Raspberry Pi device.
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