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一种基于神经网络的纳秒脉冲波形重建方法

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针对一种由高速数采通道存在寄生参数、带宽不足导致的纳秒脉冲测量波形畸变的问题,提出了一种基于神经网络的波形重建方法.通过单一神经网络辨识高速数采畸变波形与示波器参考波形的局部映射关系,通过神经网络序列完成全局波形的重建.验证实验表明所提出的方法可以明显缓解高速数采波形的边沿变缓、过冲等问题,波形功率估计精度提高32.5%,能够显著改善高速数采的频响特性.
A nano-second pulse waveform reconstruction method based on neural network
A new method of waveform reconstruction based on neural network is proposed to solve the problem of nano-second pulse distortion,which is caused by the existence of parasitic parameters and insufficient bandwidth in high-speed digital acquisition channels.The local mapping relationship between the distortion waveform acquired by the high-speed digital acquisition system and the reference waveform obtained from the oscilloscope is identified through single neural networks.Then,the global waveform is reconstructed by a series of neural networks.The experimental results show that the proposed method can obviously alleviate the problems such as the edge delay,overshoot of the distortion waveform,thus it can improve the power estimation accuracy by 32.5%,as well as improve the frequency response characteristics of the high-speed digital acquisition system.

neural networkwaveform reconstructionnanosecond pulsewaveform distortionfrequency response characteristics

吕东辉、程杰、李锐、张楠、张立刚

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西北核技术研究所,西安 710024

先进高功率微波技术重点实验室,西安 710024

神经网络 波形重建 纳秒脉冲 波形畸变 频响特性

2025

强激光与粒子束
中国工程物理研究院 中国核学会 四川核学会

强激光与粒子束

北大核心
影响因子:1.008
ISSN:1001-4322
年,卷(期):2025.37(1)