Version 1
: Received: 27 April 2024 / Approved: 28 April 2024 / Online: 29 April 2024 (10:24:50 CEST)
How to cite:
Burman, A.; Solé-Casals, J.; Lew, S. E. A Streaming Algorithm for a Fast, Robust, and Memoryless Median Estimation on Sensor Data. Preprints2024, 2024041859. https://doi.org/10.20944/preprints202404.1859.v1
Burman, A.; Solé-Casals, J.; Lew, S. E. A Streaming Algorithm for a Fast, Robust, and Memoryless Median Estimation on Sensor Data. Preprints 2024, 2024041859. https://doi.org/10.20944/preprints202404.1859.v1
Burman, A.; Solé-Casals, J.; Lew, S. E. A Streaming Algorithm for a Fast, Robust, and Memoryless Median Estimation on Sensor Data. Preprints2024, 2024041859. https://doi.org/10.20944/preprints202404.1859.v1
APA Style
Burman, A., Solé-Casals, J., & Lew, S. E. (2024). A Streaming Algorithm for a Fast, Robust, and Memoryless Median Estimation on Sensor Data. Preprints. https://doi.org/10.20944/preprints202404.1859.v1
Chicago/Turabian Style
Burman, A., Jordi Solé-Casals and Sergio E. Lew. 2024 "A Streaming Algorithm for a Fast, Robust, and Memoryless Median Estimation on Sensor Data" Preprints. https://doi.org/10.20944/preprints202404.1859.v1
Abstract
We propose a novel moving median estimator specifically designed for online detection of threshold crossings in multi-channel signals, such as extracellular neural recordings. This estimator offers two key advantages: a reduced sensitivity to outliers and the elimination of memory requirements for storing arrival times. Furthermore, its design facilitates parallel implementation on FPGAs, making it ideal for real-time processing of multi-channel recordings.
Keywords
median; estimator; on-line; neural recordings
Subject
Computer Science and Mathematics, Probability and Statistics
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
