Electronic Communication Fault Signal Recognition Based on Data Mining Algorithm

Abstract

In order to solve the technical problem of fault signal recognition in the field of communication, this paper proposes an electronic communication fault signal recognition method based on data mining algorithm. Firstly, the K-means clustering algorithm is used to determine the cluster number k according to some attributes or class characteristics of the communication class samples, and the communication sample types are classified into a certain class so that the communication sample data in the cluster can be closely distributed and the data within a certain class range can be calculated by Euclidean distance formula. Then, this paper clusters the data. In the clustering data, BP neural network model is used to train and calculate the obtained clustering data again, which can map and deal with the complex nonlinear relationship between the fault information data of different clustering categories. The results show that the final error accuracy can be raised to about 20% by using the method in this paper. Conclusion. The algorithm designed in this paper can quickly predict the factors affecting the communication and find the communication fault information.

Application of Electronic Communication Signal Modulation Recognition System Based on Fourier Transform

“…Furthermore, observing the expression for the M -WFRFT weighting coefficients given in Eq. (11) shows that the GMFRFT weighting coefficients with a term number of k satisfy periodicity:…”

“…In addition, the definition of GMFRFT given by Eq. (11) shows that the GMFRFT for any number of terms can be expressed as a weighted superposition of Fourier transforms [ ]( 0,1, 2,3)…”

“…Experimental results in the literature [10] show that an automatic acquisition system for multichannel electronic communication signals has an acquisition rate 1.0689 times higher than that of a conventional system, increasing efficiency and reducing processing time. Literature [11] provides an electronic communication method based on data mining algorithms, which can efficiently and rapidly predict the factors affecting communication and extract the information from the communication signals, and the error rate can be improved by about 20%.…”

Retracted: Electronic Communication Fault Signal Recognition Based on Data Mining Algorithm

“…This article has been retracted by Hindawi following an investigation undertaken by the publisher [1]. This investigation has uncovered evidence of one or more of the following indicators of systematic manipulation of the publication process:…”