Reconstruction of Distorted Signal with Finite Innovation Rate Based on LSTM Feature Extraction

LIU Di; QIAN Hui; WANG Zhong-feng

doi:10.12263/DZXB.20201109

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Reconstruction of Distorted Signal with Finite Innovation Rate Based on LSTM Feature Extraction

PAPERS | 更新时间：2025-12-08

- Reconstruction of Distorted Signal with Finite Innovation Rate Based on LSTM Feature Extraction
- ACTA ELECTRONICA SINICA Vol. 50, Issue 1, Pages: 217-225(2022)
- 作者机构：
  
  1.福州大学物理与信息工程学院，福建福州 350108
  2.南京大学电子科学与工程学院，江苏南京 210023
- 作者简介：
- 基金信息：
- DOI：10.12263/DZXB.20201109
  CLC： TN79;TP391.1
- Received：10 October 2020，
  
  Revised：2021-06-16，
  
  Published：25 January 2022
- 稿件说明：
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刘狄,钱慧,王中风.基于LSTM特征提取的有限新息率畸变信号重构[J].电子学报,2022,50(01):217-225.

LIU Di,QIAN Hui,WANG Zhong-feng.Reconstruction of Distorted Signal with Finite Innovation Rate Based on LSTM Feature Extraction[J].ACTA ELECTRONICA SINICA,2022,50(01):217-225.
刘狄,钱慧,王中风.基于LSTM特征提取的有限新息率畸变信号重构[J].电子学报,2022,50(01):217-225. DOI： 10.12263/DZXB.20201109.

LIU Di,QIAN Hui,WANG Zhong-feng.Reconstruction of Distorted Signal with Finite Innovation Rate Based on LSTM Feature Extraction[J].ACTA ELECTRONICA SINICA,2022,50(01):217-225. DOI： 10.12263/DZXB.20201109.

摘要

有限新息率（Finite Rate of Innovation，FRI）采样利用已知的信号波形结构实现信号的亚奈奎斯特率采样，在宽带信息系统应用中具有广泛的前景.但是，在实际的信息系统中，信号波形结构常常因噪声、远距离传输等非理想因素而发生畸变，从而导致FRI重构失败.本文依据波形再生的原理，提出了一种基于长短时记忆（Long and Short-Term Memory，LSTM）自动编码器的FRI重构方法.该方法利用LSTM自动编码器取代FRI采样系统中的采样核函数，通过离线训练获取畸变信号的未知波形结构，从而将波形序列投影为狄拉克特征序列，实现了波形畸变信号的FRI采样及重构.结果表明，本文的方法可以借助经典的零化滤波器有效地重构由于多径效应而发生畸变的FRI波形信号.

Abstract

The finite rate of innovation(FRI) samples signal at rate of sub-Nyquist rate by using the known waveform structure

which has a wide application prospect in wideband information systems. However

in the real-world information system

the signal waveform structure is often distorted by the non-ideal factors

such as noise and long-distance transmission

which leads to fail to reconstruct the FRI waveform. According to the principle of waveform regeneration

an FRI reconstruction method based on long and short-term memory(LSTM) is proposed in this paper. This method replaces the sampling kernel of FRI sampling system by an automatic LSTM encoder

and the distorted waveform with unknown structure is obtained by off-line training. Thus

the waveform sequence is projected to a Dirac signature sequence. The FRI sampling and reconstruction of waveform distortion signal are realized. The results show that the proposed method can effectively reconstruct the FRI signals

which distorted by the multipath effect

by exploiting the standard annihilating filter.

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references

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