Related Works & Resources
Performance in 1D Anomaly Detection
| Method | Precision | Recall | F1 Score |
|---|---|---|---|
| K-means | 0.89 | 0.87 | 0.88 |
| BIRCH | 0.82 | 0.85 | 0.83 |
| GMM/EM | 0.78 | 0.81 | 0.79 |
| Cortical Codex (Our Method) | 0.95 | 0.93 | 0.94 |
Resources
Latest Blog Posts and Articles
- Introduction to Cortical Codex: A New Paradigm in Anomaly Detection
Published on: May 15, 2023
- Real-time Anomaly Detection: Challenges and Solutions
Published on: June 2, 2023
- Cortical Codex vs. Traditional Methods: A Comparative Analysis
Published on: June 20, 2023
Published Research
High Performance Time Series Anomaly Detection Using Brain Inspired Cortical Codex Method
DOI: 10.1109/ACCESS.2023.3239212
Yucel, M., Sertbas, A., and Ustundag, B.
IEEE Transactions on Computers, 2023
This study presents a novel cortical Codex method for real-time anomaly detection in time series data, demonstrating improved computational efficiency and scalability over traditional clustering algorithms.
Read MoreBrain Inspired Cortical Codex Method for Fast Clustering and Codebook Generation
DOI: 10.3390/e24111678
Yucel, M., Bagis, S., Sertbas, A., Sarikaya, M., and Ustundag, B.
MDPI Entropy, 2022
This study presents a brain-inspired cortical Codex method designed to optimize both temporal efficiency and generalization in clustering and codebook generation.
Read More