IDENTIFICATION OF PULSE STREAMS OF UNKNOWN SHAPE FROM TIME ENCODING MACHINE SAMPLES

Meghna Kalra, Yoram Bresler, Kiryung Lee

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

We present an algorithm for the resolution of delayed and overlapping pulses of a common unknown shape from multichannel measurements. We show that just a few Fourier samples acquired by a Time Encoding Machine (TEM) suffice to solve this challenging problem. This acquisition scheme is desired for ultra-low power applications in wearables, such as EMG skin sensor tattoo. Numerical experiments demonstrate exact recovery of the time delays and Fourier series coefficient of the pulse shape in the noiseless case as predicted by the theory, with acceptable error in the presence of noise.

Original languageEnglish (US)
Title of host publication2022 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2022 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages5148-5152
Number of pages5
ISBN (Electronic)9781665405409
DOIs
StatePublished - 2022
Event47th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2022 - Virtual, Online, Singapore
Duration: May 23 2022May 27 2022

Publication series

NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Volume2022-May
ISSN (Print)1520-6149

Conference

Conference47th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2022
Country/TerritorySingapore
CityVirtual, Online
Period5/23/225/27/22

Keywords

  • Blind deconvolution
  • subspace method
  • superresolution
  • time encoding machine

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering

Fingerprint

Dive into the research topics of 'IDENTIFICATION OF PULSE STREAMS OF UNKNOWN SHAPE FROM TIME ENCODING MACHINE SAMPLES'. Together they form a unique fingerprint.

Cite this