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通过将 Deep Learning Toolbox™ 与 Signal Processing Toolbox™ 或 Wavelet Toolbox™ 结合使用,将深度学习应用于信号处理。有关音频和语音处理领域的应用,请参阅深度学习在音频处理领域的应用。有关无线通信中的应用,请参阅使用深度学习的无线通信


信号标注器Label signal attributes, regions, and points of interest


labeledSignalSetCreate labeled signal set
signalLabelDefinitionCreate signal label definition
signalMaskModify and convert signal masks and extract signal regions of interest
countlabelsCount number of unique labels
folders2labelsGet list of labels from folder names
splitlabelsFind indices to split labels according to specified proportions
signalDatastoreDatastore for collection of signals
dlstftDeep learning short-time Fourier transform


Deploy Signal Segmentation Deep Network on Raspberry Pi

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

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

This example shows how to generate and deploy a CUDA® executable that classifies human electrocardiogram (ECG) signals using features extracted by the continuous wavelet transform (CWT) and a pretrained convolutional neural network (CNN).

Deploy Signal Classifier Using Wavelets and Deep Learning on Raspberry Pi

This example shows the workflow to classify human electrocardiogram (ECG) signals using the Continuous Wavelet Transform (CWT) and a deep convolutional neural network (CNN).