中国电力2017，Vol.50Issue(9)：89-94,6.DOI:10.11930/j.issn.1004-9649.201606111
基于小波神经网络的低压电力线背景噪声建模
Research on Modeling of Low-Voltage Power Line Background Noise by Wavelet Neural Networks
摘要
Abstract
In order to improve anti-interference ability of power line communications,a new modeling method for colored background noise and narrowband noise based on wavelet neural network is proposed.Firstly,the background noise is modeled by wavelet neural network.The output noise waveforms and power spectrum densities (PSD) obtained from model are compared with test noise by calculating root mean square error(RMSE).Moreover,the background noise is also modeled by traditional wavelet packet transform and peak typed Markov chain.RMSEs of PSDs before and after modeling are also calculated.Simulation results show that both output noise waveforms and PSD obtained by proposed model have good agreements with test noise.The RMSE is smaller than the value generated using wavelet packet transform and peak typed Markov chain.Therefore,the proposed wavelet neural network model is effective in modeling background noise,especially for the wideband colored background noise.关键词
有色背景噪声/窄带背景噪声/小波神经网络/小波马尔科夫链Key words
colored background noise/narrowband background noise/wavelet neural network/wavelet packet transform and peak typed Markov chain分类
信息技术与安全科学引用本文复制引用
索超男,赵雄文,张慧,卢文冰..基于小波神经网络的低压电力线背景噪声建模[J].中国电力,2017,50(9):89-94,6.基金项目
国网重庆市电力公司资助项目(KH15010158)This work is supported by State Grid Chongqing Electric Power Company (No.KH15010158). （KH15010158）
