Synchronous capture method of multi-channel weak signal in long-distance communication network

Author:

Wang Yuanyuan

Abstract

In order to improve the accuracy, efficiency and network throughput of multi-channel weak signal synchronous acquisition in the network, a multi-channel weak signal synchronous acquisition method in remote communication network is designed. Firstly, by analyzing the multi-channel structure of remote communication network, the interference factors of multi-channel weak signal acquisition are determined. The parameter model method is used to estimate the bispectrum of weak signals, complete the multi-channel weak signal extraction of remote communication network, and preprocess the multi-channel weak signals of remote communication network by average filtering method. On this basis, the characteristics of multi-channel weak signals in the remote communication network are judged, and their characteristics are changed through the short time window function in the time domain, and the multi-channel weak signal synchronous catcher in the remote communication network is constructed to realize the synchronous acquisition of multi-channel weak signals in the remote communication network. The experimental results show that this method has high accuracy, short time-consuming and good network throughput. The acquisition accuracy of this method is always maintained at more than 90%.

Publisher

IOS Press

Subject

Computational Mathematics,Computer Science Applications,General Engineering

Reference18 articles.

1. Network intrusion detection using multi-architectural modular deep neural network;Atefinia;J Supercomput.,2021

2. Power information network intrusion detection based on data mining algorithm;Zuo;J Supercomput.,2020

3. Research on abnormal data detection of optical fiber communication network based on data mining;Ma;J Appl Opt.,2020

4. Memristor TCAMs Accelerate regular expression matching for network intrusion detection;Graves;IEEE Trans Nanotechnol.,2019

5. Unsupervised learning approach for network intrusion detection system using autoencoders;Choi;J Supercomput.,2020

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