Adaptive Filter for Automatic Identification of Multiple Faults in a Noisy OTDR Profile

Autor:	von der Weid, Jean Pierre, Souto, Mario H., Garcia, Joaquim D., Amaral, Gustavo C.
Rok vydání:	2016
Předmět:	Statistics - Applications Statistics - Machine Learning
Druh dokumentu:	Working Paper
DOI:	10.1109/JLT.2016.2570302
Popis:	We present a novel methodology able to distinguish meaningful level shifts from typical signal fluctuations. A two-stage regularization filtering can accurately identify the location of the significant level-shifts with an efficient parameter-free algorithm. The developed methodology demands low computational effort and can easily be embedded in a dedicated processing unit. Our case studies compare the new methodology with current available ones and show that it is the most adequate technique for fast detection of multiple unknown level-shifts in a noisy OTDR profile. Comment: 15 pages, 4 figures
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/1602.04379 Zobrazit plný text záznamu View this record from Arxiv