电信号压缩的多模型编码方案

IF 3.4 2区 工程技术 Q2 ENGINEERING, ELECTRICAL & ELECTRONIC
Corentin Presvôts , Michel Kieffer , Thibault Prevost , Patrick Panciatici , Zuxing Li , Pablo Piantanida
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引用次数: 0

摘要

提出了一种低延迟多模型编码(MMC)方法,用于在编码速率限制下压缩采样电信号波形。这种方法是基于窗口的。几个参数波形模型相互竞争,以在每个考虑的窗口中获得信号的第一个粗表示。然后,比较了不同的剩余压缩技术,使剩余重构误差最小。对模型参数进行量化,优化了两步间速率预算的分配。仿真结果表明,所提出的MMC方法在周期和瞬态信号波形上取得了比现有方法更高的信噪比。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Multiple-model coding scheme for electrical signal compression
This paper proposes a low-latency Multiple-Model Coding (MMC) approach to compress sampled electrical signal waveforms under encoding rate constraints. The approach is window-based. Several parametric waveform models are put in competition to obtain a first coarse representation of the signal in each considered window. Then, different residual compression techniques are compared to minimize the residual reconstruction error. The model parameters are quantized, and the allocation of the rate budget among the two steps is optimized. Simulation results show that the proposed MMC approach achieves a higher signal-to-noise ratio than state-of-the-art solutions on periodic and transients signal waveforms.
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来源期刊
Signal Processing
Signal Processing 工程技术-工程:电子与电气
CiteScore
9.20
自引率
9.10%
发文量
309
审稿时长
41 days
期刊介绍: Signal Processing incorporates all aspects of the theory and practice of signal processing. It features original research work, tutorial and review articles, and accounts of practical developments. It is intended for a rapid dissemination of knowledge and experience to engineers and scientists working in the research, development or practical application of signal processing. Subject areas covered by the journal include: Signal Theory; Stochastic Processes; Detection and Estimation; Spectral Analysis; Filtering; Signal Processing Systems; Software Developments; Image Processing; Pattern Recognition; Optical Signal Processing; Digital Signal Processing; Multi-dimensional Signal Processing; Communication Signal Processing; Biomedical Signal Processing; Geophysical and Astrophysical Signal Processing; Earth Resources Signal Processing; Acoustic and Vibration Signal Processing; Data Processing; Remote Sensing; Signal Processing Technology; Radar Signal Processing; Sonar Signal Processing; Industrial Applications; New Applications.
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