Kalman filter with impulse noised outliers: a robust sequential algorithm to filter data with a large number of outliers
Author:
Affiliation:
1. MISTEA, Univ Montpellier, INRAE, Institut Agro , Montpellier , France
2. SELMET, Univ Montpellier, INRAE, CIRAD, Institut Agro , Montpellier , France
Abstract
Funder
TechCare
Publisher
Walter de Gruyter GmbH
Link
https://www.degruyter.com/document/doi/10.1515/ijb-2023-0065/pdf
Reference58 articles.
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2. Pimentel, MAF, Clifton, DA, Clifton, L, Tarassenko, L. A review of novelty detection. Signal Process 2014;99:215–49. https://doi.org/10.1016/j.sigpro.2013.12.026.
3. Chandola, V, Banerjee, A, Kumar, V. Anomaly detection: a survey. ACM Comput Surv 2009;41:1–58. https://doi.org/10.1145/1541880.1541882.
4. Maity, A, Chatterjee, R. Impulsive noise in images: a brief review. Comput Vis Graph Image Process 2018;4:6–15. https://doi.org/10.19101/tipcv.2017.39025.
5. Pardeshi, V, Patil, R. Suppression of random valued impulse noise in image processing: a review. Int J Adv Res Electrical Electron Instrum Eng 2015;4. https://doi.org/10.15662/ijareeie.2015.0401017.
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