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Control Charts and Machine Learning for Anomaly Detection in Manufacturing

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Cover of 'Control Charts and Machine Learning for Anomaly Detection in Manufacturing'

Table of Contents

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    Book Overview
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    Chapter 1 Introduction to Control Charts and Machine Learning for Anomaly Detection in Manufacturing
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    Chapter 3 Control Charts for Monitoring Time-Between-Events-and-Amplitude Data
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    Chapter 4 Monitoring a BAR(1) Process with EWMA and DEWMA Control Charts
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    Chapter 5 On Approaches for Monitoring Categorical Event Series
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    Chapter 7 A Review of Tree-Based Approaches for Anomaly Detection
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    Chapter 8 Joint Use of Skip Connections and Synthetic Corruption for Anomaly Detection with Autoencoders
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    Chapter 9 A Comparative Study of $$\text {L}_1$$ L 1 and $$\text {L}_2$$ L 2 Norms in Support Vector Data Descriptions
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    Chapter 10 Feature Engineering and Health Indicator Construction for Fault Detection and Diagnostic
Attention for Chapter 8: Joint Use of Skip Connections and Synthetic Corruption for Anomaly Detection with Autoencoders
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