MathWorks MATLAB AI

Collect vibration data via sensors.

Preprocess signals using the Signal Processing Toolbox.

Extract features using Wavelet transforms.

Train a Random Forest classifier in the Classification Learner.

Deploy the model to an edge gateway using MATLAB Coder.

Capture wafer images via high-res cameras.

Use Image Labeler to mark defects (cracks, dust).

Train a YOLOv4 or ResNet network.

Optimize the network using the Deep Learning Optimizer.

Deploy to a manufacturing line GPU for real-time inspection.

Simulate traffic scenarios in Simulink.

Apply Reinforcement Learning (PPO or DDPG agents).

Train agents in a parallel cloud environment.

Test safety constraints using formal verification tools.

Export the policy to C++ for the vehicle's onboard computer.

Load raw ECG data into the Signal Analyzer.

Apply adaptive filtering for noise reduction.

Use an LSTM network for sequence classification.

Validate results against a clinical database.

Package the analysis as a standalone web app.

Access multispectral imagery from the cloud.

Train a GAN (Generative Adversarial Network) to 'paint' over clouds.

Use multi-GPU training to handle large datasets.

Verify accuracy using ground truth data.

Integrate results into a GIS mapping system.

Import historical market data from Bloomberg/Refinitiv.

Apply GARCH models and Deep Learning regression.

Perform Monte Carlo simulations for VaR (Value at Risk).

Automate report generation using MATLAB Report Generator.

Share results with stakeholders via MATLAB Web App Server.

Gather battery cell voltage and current data.

Use the Battery Pack Model block to simulate aging.

Train a feed-forward neural network on the discharge curves.

Convert the model to Fixed-Point math for the BMS microcontroller.

Test for safety-critical hardware-in-the-loop (HIL).