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.
Authors
- Zuxing Li (ORCID: https://orcid.org/0000-0002-2276-2079)
- Patrick Panciatici (ORCID: https://orcid.org/0009-0000-8936-094X)
- Thibault Prévost (ORCID: https://orcid.org/0000-0001-8129-5813)
- Pablo Piantanida (ORCID: https://orcid.org/0000-0002-8717-2117)
- Michel Kieffer (ORCID: https://orcid.org/0000-0002-1049-3123)
- Corentin Presvôts (ORCID: https://orcid.org/0009-0009-7552-3459)
Institutions
- Centre National de la Recherche Scientifique (FR)
- Université Paris-Saclay (FR)
- CentraleSupélec (FR)
- Électricité de France (France) (FR)
Publication Details
- Journal
- Signal Processing
- Published
- 2025-04-18
- DOI
- https://doi.org/10.1016/j.sigpro.2025.110037
- Primary Topic
- Advanced Data Compression Techniques
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Association Nationale de la Recherche et de la Technologie