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Detecting Non-Overlapping Signals with Dynamic Programming.
- Source :
-
Entropy (Basel, Switzerland) [Entropy (Basel)] 2023 Jan 30; Vol. 25 (2). Date of Electronic Publication: 2023 Jan 30. - Publication Year :
- 2023
-
Abstract
- This paper studies the classical problem of detecting the locations of signal occurrences in a one-dimensional noisy measurement. Assuming the signal occurrences do not overlap, we formulate the detection task as a constrained likelihood optimization problem and design a computationally efficient dynamic program that attains its optimal solution. Our proposed framework is scalable, simple to implement, and robust to model uncertainties. We show by extensive numerical experiments that our algorithm accurately estimates the locations in dense and noisy environments, and outperforms alternative methods.
Details
- Language :
- English
- ISSN :
- 1099-4300
- Volume :
- 25
- Issue :
- 2
- Database :
- MEDLINE
- Journal :
- Entropy (Basel, Switzerland)
- Publication Type :
- Academic Journal
- Accession number :
- 36832618
- Full Text :
- https://doi.org/10.3390/e25020250