Signal Processing Using Deep Learning

Extend deep learning workflows with signal processing and communications applications

Apply deep learning to signal processing and communications applications by using Deep Learning Toolbox™ together with Signal Processing Toolbox™, Wavelet Toolbox™, and Communications Toolbox™. For audio and speech processing applications, see Audio Processing Using Deep Learning.

Topics

Classify ECG Signals Using Long Short-Term Memory Networks

This example shows how to classify heartbeat electrocardiogram (ECG) data from the PhysioNet 2017 Challenge using deep learning and signal processing.

Classify Time Series Using Wavelet Analysis and Deep Learning

This example shows how to classify human electrocardiogram (ECG) signals using the continuous wavelet transform (CWT) and a deep convolutional neural network (CNN).

Modulation Classification with Deep Learning

This example shows how to use a convolutional neural network (CNN) for modulation classification.

Waveform Segmentation Using Deep Learning

This example shows how to segment human electrocardiogram (ECG) signals using recurrent deep learning networks and time-frequency analysis.

Featured Examples