Exploiting self-similarity for change detection

@article{Boracchi2014ExploitingSF,
  title={Exploiting self-similarity for change detection},
  author={Giacomo Boracchi and Manuel Roveri},
  journal={2014 International Joint Conference on Neural Networks (IJCNN)},
  year={2014},
  pages={3339-3346}
}
Time-series data are often characterized by a large degree of self-similarity, which arises in application domains featuring periodicity or seasonality. While self-similarity has shown to be an effective prior for modeling real data in the signal and image-processing literature, it has received much less attention in time-series literature, where only few works leveraging the self-similarity for anomaly detection have been presented. Here we introduce a novel change-detection test to detect… CONTINUE READING
Highly Cited
This paper has 40 citations. REVIEW CITATIONS

6 Figures & Tables

Topics

Statistics

0102030201620172018
Citations per Year

Citation Velocity: 13

Averaging 13 citations per year over the last 3 years.

Learn more about how we calculate this metric in our FAQ.