Apply statistics and machine learning methods to industry-specific
workflows
Aerospace
Radar Target Classification Using Machine Learning and Deep Learning (Radar Toolbox)
Classify radar returns using machine and deep learning approaches. (Since R2021a)
Communications and Signal Processing
Data Analysis on S-Parameters of RF Data Files (RF Toolbox)
Perform statistical analysis on S-parameter data files using magnitude, mean, and
standard deviation.
Wavelet Time Scattering with GPU Acceleration — Spoken Digit Recognition (Wavelet Toolbox)
Extract features on your GPU for signal classification.
Feature Selection for Audio Classification (Audio Toolbox)
Perform audio feature selection to select a feature set for either speaker recognition
or word recognition tasks.
Speaker Identification Using Pitch and MFCC (Audio Toolbox)
Use machine learning to identify people based on features extracted from recorded
speech.
Speaker Diarization Using x-vectors (Audio Toolbox)
Speaker diarization is the process of partitioning an audio signal into segments according to speaker identity.
Accelerate Audio Machine Learning Workflows Using a GPU (Audio Toolbox)
This example shows how to use GPU computing to accelerate machine learning workflows for audio, speech, and acoustic applications. (Since R2024a)
Generate Synthetic Signals Using Conditional GAN (Signal Processing Toolbox)
Use a conditional generative adversarial network to produce synthetic signals.
Human Activity Recognition Using Signal Feature Extraction and Machine Learning (Signal Processing Toolbox)
Extract features from smartphone sensor signals and use them to classify human
activity.
Industrial Automation and Machinery
Fault Detection Using Data Based Models (Predictive Maintenance Toolbox)
Use a data-based modeling approach for fault detection.
Anomaly Detection in Industrial Machinery Using Three-Axis Vibration Data (Predictive Maintenance Toolbox)
Detect anomalies in industrial-machine vibration data using machine learning and deep
learning.
Build Condition Model for Industrial Machinery and Manufacturing Processes
Train a binary classification model using Classification Learner App to detect
anomalies in sensor data collected from an industrial manufacturing
machine.
Rolling Element Bearing Fault Diagnosis (Predictive Maintenance Toolbox)
Perform fault diagnosis of a rolling element bearing based on acceleration
signals.
Fault Diagnosis of Centrifugal Pumps Using Residual Analysis (Predictive Maintenance Toolbox)
Use a model parity-equations-based approach for detection and diagnosis of faults in a
pumping system.
Air Compressor Fault Detection Using Wavelet Scattering (Wavelet Toolbox)
Classify faults in acoustic recordings of air compressors using a wavelet
scattering network and a support vector machine. (Since R2021b)
Predict Battery State of Charge Using Machine Learning
Train a Gaussian process regression model to predict the state of charge of a
battery in automotive engineering.
Deploy Neural Network Regression Model to FPGA/ASIC Platform
Predict in Simulink® using a neural network regression model, and deploy the Simulink model to an FPGA/ASIC platform by using HDL code generation.
Monitor Equipment State of Health Using Drift-Aware Learning
This example shows how to automate the process of monitoring the state of health for a cooling system using an incremental drift-aware learning model and Streaming Data Framework for MATLAB® Production Server™.
Monitor Equipment State of Health Using Drift-Aware Learning on the Cloud
This example describes the set up necessary to run the deployed version of the Monitor Equipment State of Health Using Drift-Aware Learning example on the cloud.
Medical Devices
Wavelet Time Scattering for ECG Signal Classification (Wavelet Toolbox)
Classify human electrocardiogram signals using wavelet time scattering and a
support vector machine classifier.
Wavelet Time Scattering Classification of Phonocardiogram Data (Wavelet Toolbox)
Classify human phonocardiogram recordings using wavelet time scattering and a
support vector machine classifier.
Human Activity Recognition Simulink Model for Smartphone Deployment
Generate code from a classification Simulink model prepared for deployment to a smartphone.
Human Activity Recognition Simulink Model for Fixed-Point Deployment
Generate code from a classification Simulink model prepared for fixed-point deployment.