Signal Processing
Extend deep learning workflows with signal processing applications
Apply deep learning to signal processing by using Deep Learning Toolbox™ together with Signal Processing Toolbox™, Wavelet Toolbox™, or DSP System Toolbox™. For audio and speech processing applications, see Audio Processing. For radar processing applications, see Radar Processing. For applications in wireless communications, see Wireless Communications.
Categories
- Classification
Classify signal attributes, perform signal segmentation via sequence-to-sequence classification
- Regression
Signal denoising, phase recovery, and source separation
- Preprocessing and Feature Extraction
Extract signal features in time, frequency, and time-frequency domains
- Signal Labeling
Manual and automated labeling of signal attributes, regions of interest, and points
- Anomaly Detection
Detect signal anomalies using AI models, including deep learning networks
- Embedded AI Systems
Deploy deep learning into embedded targets and GPUs