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ED-FreEst: Event-driven frequency estimation
File(s)
Author(s)
Guo, Ruiming
Bhandari, Ayush
Type
Conference Paper
Abstract
Event-driven or Time-encoded sampling is an alternative to the conventional uniform sampling paradigm that encodes the amplitude information of a continuous-time signal into a sequence of time stamps. The data-driven approach of event-driven acquisition provides significant power efficiency advantages, as it initiates sampling exclusively upon the detection of specific events, such as amplitude changes. In recent years, the focus of event-driven sampling has shifted from bandlimited function classes to time-domain sparse signals. That said, the case of Fourier-domain sparse signals (frequency or spectral estimation problem) remains open. In this paper, we introduce a novel method for off-the-grid, event-driven frequency estimation (ED-FreEst). Empirically, our algorithm results in a lower sampling rate while offering robustness. These aspects seamlessly translate into real-world validation. To demonstrate this, we build an event-driven sampling hardware utilizing asynchronous sigma-delta modulators, showcasing the practical utility and effectiveness of our method in tangible applications.
Date Issued
2024-10-23
Date Acceptance
2024-08-01
Citation
2024 32nd European Signal Processing Conference (EUSIPCO), 2024, pp.867-871
URI
DOI
ISBN
979-8-3315-1977-3
ISSN
2076-1465
Publisher
IEEE
Start Page
867
End Page
871
Journal / Book Title
2024 32nd European Signal Processing Conference (EUSIPCO)
Copyright Statement
© 2024 EUSIPCO. This is the author’s accepted manuscript made available under a CC-BY licence in accordance with Imperial’s Research Publications Open Access policy (www.imperial.ac.uk/oa-policy)
License URL
Source
32nd European Signal Processing Conference (EUSIPCO)
Subjects
Computer Science
Computer Science, Software Engineering
Engineering
Engineering, Electrical & Electronic
Event-driven
frequency estimation
nonuniform sampling
RECOVERY
Science & Technology
Technology
Telecommunications
TIME
time-encoded sampling
Publication Status
Published
Start Date
2024-08-26
Finish Date
2024-08-30
Coverage Spatial
Lyon, France