1 INTRODUCTION

2 BACKGROUND

2.1 Univariate Time Series

2.2 Multivariate Time Series

2.3 Time Series Decomposition

2.4 Anomalies in Time Series

3 TIME SERIES ANOMALY DETECTION METHODS

3.1 Deep Models for Time Series Anomaly Detection

3.2 Forecasting-Based Models

3.3 Reconstruction-Based Models

3.4 Representation-Based Models

3.5 Hybrid Models

3.6 Model Selection Guidelines for Time Series Anomaly Detection

4 DATASETS

5 DISCUSSION AND CONCLUSION