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AI for Signal Processing

Build and deploy domain-specific AI systems that process and model signals

Artificial intelligence (AI) offers new opportunities to improve signal processing systems for various real-world signals, such as biomedical and audio. You can use MATLAB products to interactively explore, create, and preprocess data, engineer features, build AI models, and deploy AI systems.

Why MATLAB?

Apps for Signal Processing and Labeling

Use low-code apps to improve data quality through exploration, analysis, preprocessing, and automatic labeling of the ground truth.

Signal Analyzer App

Signal Labeler App

AI Models

Create AI models with machine learning and deep learning algorithms or use pretrained models.

Pretrained Deep Learning Models

Introduction to Deep Learning: Machine Learning vs. Deep Learning (3:47)

Feature Extraction

Engineer features from signals using feature extraction (pca, wavelet scattering) or time-frequency transformations (spectrogram, wavelet transform).

Audio Feature Extractor

Deep Learning for Engineers, Part 3: Data Preprocessing and the Short-Time Fourier Transform (15:31)

Deploy AI-Powered Systems

Simulate and deploy your domain-specific AI systems to embedded hardware, enterprise systems, or the cloud.

MATLAB and Simulink for Edge AI

Deep Learning in the Cloud

Using AI for Signal Processing with MATLAB

Whether you are new to AI for signal processing or designing comprehensive AI systems, explore these tutorials, examples, and courses to advance your skills and help you with your next project.