Open AccessUnderwater Detection Signal Based on LM-BP Neural Network Algorithm
Author(s) -
Xiaoqing Gu,
Jingjun Lou,
Kai Liu,
Ping Hu
Publication year - 2020
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 - 10.1088/1742-6596/1533/3/032035
Subject(s) - underwater , signal (programming language) , artificial neural network , algorithm , computer science , filter (signal processing) , detection theory , underwater acoustic communication , noise (video) , artificial intelligence , telecommunications , computer vision , geology , detector , image (mathematics) , programming language , oceanography
The algorithm of underwater signal detection based on LM-BP neural network has a very broad application prospect. It is an important means of underwater background weak signal detection and a good method of phase space reconstruction. In this paper, the band-pass LM algorithm combined with BP neural network is used to process the underwater signal, which can effectively filter the magnetic noise in the underwater environment and extract the characteristics of the underwater detection signal. This paper first analyzes the time-frequency characteristics of the underwater detection signal, then studies the BP neural network of LM algorithm, and studies the design of band-pass filter, finally analyzes the application example based on LM-BP algorithm.