基于联合估计的无线通信网络干扰抑制算法  

Simulation of Multi-Feature Detail Recognition of Exposed Image Based on Filtering Algorithm

作　　者：李宁 王颖 LI Ning;WANG Ying(Department of Network Security,Shanxi Police College,Taiyuan Shanxi 030401,China;College of Information and Computer Taiyuan University of Technology,Jinzhong Shanxi 030600,China)

机构地区：[1]山西警察学院网络安全保卫系,山西太原030401 [2]太原理工大学信息与计算机学院,山西晋中030600

出　　处：《计算机仿真》2023年第12期337-341,567,共6页Computer Simulation

摘　　要：为解决无线通信网络信号不稳定导致的信息传递错误问题,提出无线通信网络干扰信号识别抑制联合估计算法消除无线通讯网络中的干扰信号。通过建立基于支持向量回归的干扰信号识别模型,有效的识别干扰信号类型,再构建基于网络抑制的干扰信号抑制模型,消除干扰信号带来的噪声。联合仿真结果表明,基于支持向量回归的干扰信号识别抑制联合估计模型对四类干扰信号识别准确率超过99%,且针对四类干扰信号,网络干扰抑制算法明显优于传统干扰抑制方法。基于干扰信号识别抑制联合估计算法有效地提高了无线通信网络的抗干扰能力,增强信息传递的稳定性。In order to solve the problem of information transmission errors caused by the instability of wireless communication network signals,this paper proposes a joint estimation algorithm for the identification and suppression of interference signals in wireless communication networks to eliminate interference signals in wireless communication networks.The interference signal identification model based on support vector regression was established to effectively identify the types of interference signals,and then the interference signal suppression model based on network suppression was constructed to eliminate the noise caused by interference signals.The joint simulation results show that the joint estimation model of interference signal identification and suppression based on support vector regression has an accuracy of more than 99%for the four types of interference signals,and the network interference suppression algorithm is significantly better than the traditional interference suppression methods for the four types of interference signals.Therefore,the joint estimation algorithm based on interference signal identification and suppression effectively improves the anti-interference ability of wireless communication networks and enhances the stability of information transmission.

关 键 词：干扰信号仿真 干扰信号识别 干扰信号抑制 

分 类 号：TP181[自动化与计算机技术—控制理论与控制工程]