Corentin Presvôts , Michel Kieffer , Thibault Prevost , Patrick Panciatici , Zuxing Li , Pablo Piantanida
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引用次数: 0
Abstract
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.
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.