使用深度学习进行信号分类

Introduction

Get an overview of the course.

课程：

Course Overview

Outline and Learning Outcomes

Course Example: Classify Flooding Severity

Import Signals in Labeled Subfolders

Use datastores to import signals and their corresponding labels.

课程：

Import Signals with a Datastore

Import Signal Labels

Visualize Signal Data Set

Read in Data Set that Fits in Memory

Prepare Training Inputs

Create all the components needed to train a signal classification network.

课程：

Training Inputs

Train, Test, and Validation Data

Recurrent Networks

Create LSTM Architecture

Training Options

Train and Evaluate a Signal Classification Network

Train a deep network for signal classification using basic inputs. Then predict with the network and evaluate its performance.

课程：

Network Training Function

Train the Network

Evaluate Network

Adjust Training Inputs to Improve the Network

Learn techniques to improve your deep network, focusing on techniques that are specific to signal applications.

课程：

Improve Network Performance Overview

Impact of Sequence Length

Standardize Sequence Length

Epochs and Mini Batches

Bidirectional Recurrent Layers

Adjust Training Inputs

Conclusion

Learn next steps and give feedback on the course.

课程：

Summary

Additional Resources

Survey

课程模块

Introduction

Import Signals in Labeled Subfolders

Prepare Training Inputs

Train and Evaluate a Signal Classification Network

Adjust Training Inputs to Improve the Network

Conclusion

语言

带自动反馈的实操练习
通过 Web 浏览器访问 MATLAB
可共享的进度报告和课程证书

深度学习入门之旅

使用深度学习进行信号分割

MATLAB 入门之旅

使用深度学习进行信号分类

课程模块

Introduction

Import Signals in Labeled Subfolders

Prepare Training Inputs

Train and Evaluate a Signal Classification Network

Adjust Training Inputs to Improve the Network

Conclusion

语言

带自动反馈的实操练习通过 Web 浏览器访问 MATLAB可共享的进度报告和课程证书

深度学习入门之旅

使用深度学习进行信号分割

MATLAB 入门之旅

带自动反馈的实操练习
通过 Web 浏览器访问 MATLAB
可共享的进度报告和课程证书