基于改进去噪自编码器的电力线信道传输特性识别实现  

Realization of Power Line Channel Transmission Characteristics Identification Based on Improved Denoising Auto-Encoder

作　　者：胡正伟[1] 赵然 陈维寅 谢志远[1] HU Zhengwei;ZHAO Ran;CHEN Weiyin;XIE Zhiyuan(School of Electrical and Electronic Engineering,North China Electric Power University,Baoding 071003,China)

机构地区：[1]华北电力大学电气与电子工程学院,河北保定071003

出　　处：《电力信息与通信技术》2021年第9期86-92,共7页Electric Power Information and Communication Technology

基　　金：国家自然基金面上项目(52177083);国家自然科学基金青年科学基金项目(62001166);河北省自然科学基金青年科学基金项目(E2019502186)。

摘　　要：文章提出了一种改进的去噪自编码器,提高了带噪电力线信道传输特性样本的识别成功率。所提方案以一维时间序列代替二维图片作为输入,改进了传统自编码器的处理数据网络结构,引入z-score标准化及对应的反标准化对输入输出信号进行处理,在提高去噪能力的同时加快了收敛速度。选取包含2个隐含层的4层神经网络从软件模型及硬件实现2个方面验证了所提方法的有效性。An improved de-noising auto-encoder is proposed to improve the recognition success rate of transmission characteristic in noisy power line channel.The proposed scheme uses one-dimensional time series instead of two-dimensional images as input,which improves the processing data network structure of traditional self-encoder.The introduction of Z-score standardization and corresponding antistandardization to the input and output signal processing can improve the de-noising ability and speed up the convergence speed.One 4 layers neural network with two hidden layers is selected to verify the effectiveness of the proposed method from two aspects of software model and hardware implementation.

关 键 词：电力线通信 去噪自编码 标准化 传输特性 神经网络 

分 类 号：TN915.853[电子电信—通信与信息系统]