Timothée Maison , Fabrice Silva , Nathalie Henrich Bernardoni , Philippe Guillemain
{"title":"High-order chirplet transform for efficient reconstruction of multicomponent signals with amplitude modulated crossing ridges","authors":"Timothée Maison , Fabrice Silva , Nathalie Henrich Bernardoni , Philippe Guillemain","doi":"10.1016/j.sigpro.2025.109887","DOIUrl":null,"url":null,"abstract":"<div><div>Multicomponent signals with crossing ridges, such as those encountered when measuring vocal tract resonances during singing, are challenging to analyze in time–frequency domain. The chirplet transform introduces the chirprate as a third dimension, extending the time–frequency domain to enable the separation of ridges. While existing methods assume weak amplitude modulations of signal components for the reconstruction process, a high-order chirplet transform is developed to accurately and efficiently retrieve amplitude modulation of crossing components, assuming that the instantaneous frequency of the components are already known. Analytical solving and numerical stability are obtained with a family of chirplet windows based on Hermite polynomials. The numerical results on simulated and real signals show the relevance and efficiency of the proposed method.</div></div>","PeriodicalId":49523,"journal":{"name":"Signal Processing","volume":"231 ","pages":"Article 109887"},"PeriodicalIF":3.4000,"publicationDate":"2025-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Signal Processing","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0165168425000027","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
引用次数: 0
Abstract
Multicomponent signals with crossing ridges, such as those encountered when measuring vocal tract resonances during singing, are challenging to analyze in time–frequency domain. The chirplet transform introduces the chirprate as a third dimension, extending the time–frequency domain to enable the separation of ridges. While existing methods assume weak amplitude modulations of signal components for the reconstruction process, a high-order chirplet transform is developed to accurately and efficiently retrieve amplitude modulation of crossing components, assuming that the instantaneous frequency of the components are already known. Analytical solving and numerical stability are obtained with a family of chirplet windows based on Hermite polynomials. The numerical results on simulated and real signals show the relevance and efficiency of the proposed method.
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.