摘要翻译:
本文利用嵌套低密度生成矩阵(LDGM)和低密度奇偶校验(LDPC)码,设计了一种实用的二进制Wyner-Ziv(WZ)问题的编码方案。该方案在编码过程中包含两个步骤。第一步是利用LDGM码进行二值量化,第二步是利用LDPC码进行综合症编码。该方案的译码算法基于和积(SP)算法,并借助解码器端可用的边信息。理论分析表明,该化合物结构具有达到WZ界的能力。该方法通过在编码和解码中使用迭代消息传递算法来逼近这个界限,尽管理论结果表明它是渐近可达的。
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英文标题:
《A Binary Wyner-Ziv Code Design Based on Compound LDGM-LDPC Structures》
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作者:
Mahdi Nangir, Mahmoud Ahmadian-Attari, and Reza Asvadi
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最新提交年份:
2017
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分类信息:
一级分类:Electrical Engineering and Systems Science 电气工程与系统科学
二级分类:Signal Processing 信号处理
分类描述:Theory, algorithms, performance analysis and applications of signal and data analysis, including physical modeling, processing, detection and parameter estimation, learning, mining, retrieval, and information extraction. The term "signal" includes speech, audio, sonar, radar, geophysical, physiological, (bio-) medical, image, video, and multimodal natural and man-made signals, including communication signals and data. Topics of interest include: statistical signal processing, spectral estimation and system identification; filter design, adaptive filtering / stochastic learning; (compressive) sampling, sensing, and transform-domain methods including fast algorithms; signal processing for machine learning and machine learning for signal processing applications; in-network and graph signal processing; convex and nonconvex optimization methods for signal processing applications; radar, sonar, and sensor array beamforming and direction finding; communications signal processing; low power, multi-core and system-on-chip signal processing; sensing, communication, analysis and optimization for cyber-physical systems such as power grids and the Internet of Things.
信号和数据分析的理论、算法、性能分析和应用,包括物理建模、处理、检测和参数估计、学习、挖掘、检索和信息提取。“信号”一词包括语音、音频、声纳、雷达、地球物理、生理、(生物)医学、图像、视频和多模态自然和人为信号,包括通信信号和数据。感兴趣的主题包括:统计信号处理、谱估计和系统辨识;滤波器设计;自适应滤波/随机学习;(压缩)采样、传感和变换域方法,包括快速算法;用于机器学习的信号处理和用于信号处理应用的机器学习;网络与图形信号处理;信号处理中的凸和非凸优化方法;雷达、声纳和传感器阵列波束形成和测向;通信信号处理;低功耗、多核、片上系统信号处理;信息物理系统的传感、通信、分析和优化,如电网和物联网。
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英文摘要:
In this paper, a practical coding scheme is designed for the binary Wyner-Ziv (WZ) problem by using nested low-density generator-matrix (LDGM) and low-density parity-check (LDPC) codes. This scheme contains two steps in the encoding procedure. The first step involves applying the binary quantization by employing LDGM codes and the second one is using the syndrome-coding technique by utilizing LDPC codes. The decoding algorithm of the proposed scheme is based on the Sum-Product (SP) algorithm with the help of a side information available at the decoder side. It is theoretically shown that the compound structure has the capability of achieving the WZ bound. The proposed method approaches this bound by utilizing the iterative message-passing algorithms in both encoding and decoding, although theoretical results show that it is asymptotically achievable.
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PDF链接:
https://arxiv.org/pdf/1710.07985


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