Detecting Non-Overlapping Signals with Dynamic Programming
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 dy...
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2023-01-01
|
| Series: | Entropy |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1099-4300/25/2/250 |
| _version_ | 1797621143163633664 |
|---|---|
| author | Mordechai Roth Amichai Painsky Tamir Bendory |
| author_facet | Mordechai Roth Amichai Painsky Tamir Bendory |
| author_sort | Mordechai Roth |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-03-11T08:51:30Z |
| format | Article |
| id | doaj.art-12a24c9c238c40a3bc26f04d5078c837 |
| institution | Directory Open Access Journal |
| issn | 1099-4300 |
| language | English |
| last_indexed | 2024-03-11T08:51:30Z |
| publishDate | 2023-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Entropy |
| spelling | doaj.art-12a24c9c238c40a3bc26f04d5078c8372023-11-16T20:22:54ZengMDPI AGEntropy1099-43002023-01-0125225010.3390/e25020250Detecting Non-Overlapping Signals with Dynamic ProgrammingMordechai Roth0Amichai Painsky1Tamir Bendory2School of Electrical Engineering, Tel Aviv University, Tel Aviv 6997801, IsraelThe Industrial Engineering Department, Tel Aviv University, Tel Aviv 6997801, IsraelSchool of Electrical Engineering, Tel Aviv University, Tel Aviv 6997801, IsraelThis 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.https://www.mdpi.com/1099-4300/25/2/250dynamic programmingdetection theorygap statistics |
| spellingShingle | Mordechai Roth Amichai Painsky Tamir Bendory Detecting Non-Overlapping Signals with Dynamic Programming Entropy dynamic programming detection theory gap statistics |
| title | Detecting Non-Overlapping Signals with Dynamic Programming |
| title_full | Detecting Non-Overlapping Signals with Dynamic Programming |
| title_fullStr | Detecting Non-Overlapping Signals with Dynamic Programming |
| title_full_unstemmed | Detecting Non-Overlapping Signals with Dynamic Programming |
| title_short | Detecting Non-Overlapping Signals with Dynamic Programming |
| title_sort | detecting non overlapping signals with dynamic programming |
| topic | dynamic programming detection theory gap statistics |
| url | https://www.mdpi.com/1099-4300/25/2/250 |
| work_keys_str_mv | AT mordechairoth detectingnonoverlappingsignalswithdynamicprogramming AT amichaipainsky detectingnonoverlappingsignalswithdynamicprogramming AT tamirbendory detectingnonoverlappingsignalswithdynamicprogramming |