Open AccessConvolutional neural networks for solving problems of signal processing from segmental distributed fiber optic measuring networks
Author(s) -
Yu. N. Kulchin,
A.Yu. Kim
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1864/1/012136
Subject(s) - convolutional neural network , computer science , artificial neural network , signal processing , signal (programming language) , optical fiber , artificial intelligence , speech recognition , pattern recognition (psychology) , telecommunications , computer hardware , digital signal processing , programming language
The work is devoted to the problem of critical situations recognition in real-time and localization of increased acoustic vibration in critical objects, based on the signals from segmental distributed fiber-optic measuring networks (DFOMN). To solve the problem, an architecture is proposed, and a model of a situational approach to using the Convolutional Neural Network as an effective classification method for processing large data arrays of the DFOMN is developed.