Feature Extraction Techniques for Signals

Course modules

Introduction

Get an overview of the course.

Lessons:

Course Overview

Learning Outcomes and Prerequisites

Course Example: Features from Flood Signals

Explore Signals

Analyze signals in both the time and frequency domains to identify potential features of the signal.

Lessons:

Explore the Signal in the Time Domain

Explore the Signal Spectrum

Extract Signal Features

Extract key features from signals in both the time and frequency domains.

Lessons:

Types of Signal Features

Extract Time-Domain Features

Extract Frequency-Domain Features

Extract Features from Multiple Signals

Extract relevant features from multiple signals and organize them into a structured table for further analysis.

Lessons:

Import Signals with a Datastore

Extract Features from Multiple Signals

Add Labels to Feature Table

Extract Features from Time-Varying Signals

Create feature extractor objects for specific signal segments to extract the essential characteristics of time-varying signals.

Lessons:

Signal Segmentation

Visualize the Time-Varying Labeled Signal

Choose Frame Size

Create a Feature Extractor Object for Signal Segments

Partition the Label Sequence

Extract Wavelet Features

Evaluate the Features

Analyze and evaluate the extracted signal features by identifying patterns and assessing feature relevance through ranking algorithms.

Lessons:

Find Patterns in Extracted Features

Check Feature Relevance by Ranking

Conclusion

Learn the next steps and give feedback on the course.

Lessons:

Summary

Additional Resources

Survey

Course modules

Introduction

Explore Signals

Extract Signal Features

Extract Features from Multiple Signals

Extract Features from Time-Varying Signals

Evaluate the Features

Conclusion

Language

Hands-on exercises with automated feedback
Access to MATLAB through your web browser
Shareable progress report and course certificate

Dimensionality Reduction Techniques

Signal Classification with Deep Learning

Signal Processing Onramp

Feature Extraction Techniques for Signals

Course modules

Introduction

Explore Signals

Extract Signal Features

Extract Features from Multiple Signals

Extract Features from Time-Varying Signals

Evaluate the Features

Conclusion

Language

Hands-on exercises with automated feedbackAccess to MATLAB through your web browserShareable progress report and course certificate

Dimensionality Reduction Techniques

Signal Classification with Deep Learning

Signal Processing Onramp

Hands-on exercises with automated feedback
Access to MATLAB through your web browser
Shareable progress report and course certificate