Matches in SemOpenAlex for { <https://semopenalex.org/work/W4322005966> ?p ?o ?g. }
Showing items 1 to 80 of
80
with 100 items per page.
- W4322005966 abstract "We present an improvement of the Multi-Channel Maximum-Likelihood (MCML) method [1]. This approach is based on the likelihood function derived from a multi-sensor stochastic model expressed in different frequency channels. Using the likelihood function, we determine, for the detection problem, the Generalized Likelihood Ratio (GLR) with a p-value threshold to discriminate signal of interest and noise. For the estimation of the slowness vector, we determine the Maximum Likelihood Estimation (MLE). Comparisons with synthetic and real datasets show that MCML, when implemented in the time-frequency domain, outperforms state-of-the-art detection algorithms in terms of detection probability and false alarm rate in poor signal-to-noise ratio scenarios. We evaluate the capability of MCML to detect overlapping coherent signals in the same time frequency domain, depending on various scenarios with varying signal-to-noise ratio (SNR), frequency bands and array geometry. We quantify the performance of deep learning method to discriminate between interfering coherent signals by predicting the number of sources in a given time-frequency cell using synthetics and real data recorded by stations part of the International Monitoring System (IMS). [1] B Poste, M Charbit, A Le Pichon, C Listowski, F Roueff, J Vergoz (2022), The Multi-Channel Maximum-Likelihood (MCML) method: a new approach for infrasound detection and wave parameter estimation, Geophysical Journal International, https://doi.org/10.1093/gji/ggac377" @default.
- W4322005966 created "2023-02-26" @default.
- W4322005966 creator A5024071636 @default.
- W4322005966 creator A5034132911 @default.
- W4322005966 creator A5039877564 @default.
- W4322005966 creator A5052594536 @default.
- W4322005966 creator A5067480887 @default.
- W4322005966 creator A5073675112 @default.
- W4322005966 creator A5078093714 @default.
- W4322005966 date "2023-05-15" @default.
- W4322005966 modified "2023-09-29" @default.
- W4322005966 title "The Multi-Channel Maximum-Likelihood (MCML) method: towards a multisource detection and wave parameter estimations using deep learning" @default.
- W4322005966 doi "https://doi.org/10.5194/egusphere-egu23-6647" @default.
- W4322005966 hasPublicationYear "2023" @default.
- W4322005966 type Work @default.
- W4322005966 citedByCount "0" @default.
- W4322005966 crossrefType "posted-content" @default.
- W4322005966 hasAuthorship W4322005966A5024071636 @default.
- W4322005966 hasAuthorship W4322005966A5034132911 @default.
- W4322005966 hasAuthorship W4322005966A5039877564 @default.
- W4322005966 hasAuthorship W4322005966A5052594536 @default.
- W4322005966 hasAuthorship W4322005966A5067480887 @default.
- W4322005966 hasAuthorship W4322005966A5073675112 @default.
- W4322005966 hasAuthorship W4322005966A5078093714 @default.
- W4322005966 hasConcept C105795698 @default.
- W4322005966 hasConcept C11413529 @default.
- W4322005966 hasConcept C115961682 @default.
- W4322005966 hasConcept C127162648 @default.
- W4322005966 hasConcept C137270730 @default.
- W4322005966 hasConcept C13944312 @default.
- W4322005966 hasConcept C153180895 @default.
- W4322005966 hasConcept C154945302 @default.
- W4322005966 hasConcept C167928553 @default.
- W4322005966 hasConcept C19118579 @default.
- W4322005966 hasConcept C2776836416 @default.
- W4322005966 hasConcept C31972630 @default.
- W4322005966 hasConcept C33923547 @default.
- W4322005966 hasConcept C41008148 @default.
- W4322005966 hasConcept C76155785 @default.
- W4322005966 hasConcept C77052588 @default.
- W4322005966 hasConcept C89106044 @default.
- W4322005966 hasConcept C9483764 @default.
- W4322005966 hasConcept C94915269 @default.
- W4322005966 hasConcept C99498987 @default.
- W4322005966 hasConceptScore W4322005966C105795698 @default.
- W4322005966 hasConceptScore W4322005966C11413529 @default.
- W4322005966 hasConceptScore W4322005966C115961682 @default.
- W4322005966 hasConceptScore W4322005966C127162648 @default.
- W4322005966 hasConceptScore W4322005966C137270730 @default.
- W4322005966 hasConceptScore W4322005966C13944312 @default.
- W4322005966 hasConceptScore W4322005966C153180895 @default.
- W4322005966 hasConceptScore W4322005966C154945302 @default.
- W4322005966 hasConceptScore W4322005966C167928553 @default.
- W4322005966 hasConceptScore W4322005966C19118579 @default.
- W4322005966 hasConceptScore W4322005966C2776836416 @default.
- W4322005966 hasConceptScore W4322005966C31972630 @default.
- W4322005966 hasConceptScore W4322005966C33923547 @default.
- W4322005966 hasConceptScore W4322005966C41008148 @default.
- W4322005966 hasConceptScore W4322005966C76155785 @default.
- W4322005966 hasConceptScore W4322005966C77052588 @default.
- W4322005966 hasConceptScore W4322005966C89106044 @default.
- W4322005966 hasConceptScore W4322005966C9483764 @default.
- W4322005966 hasConceptScore W4322005966C94915269 @default.
- W4322005966 hasConceptScore W4322005966C99498987 @default.
- W4322005966 hasLocation W43220059661 @default.
- W4322005966 hasOpenAccess W4322005966 @default.
- W4322005966 hasPrimaryLocation W43220059661 @default.
- W4322005966 hasRelatedWork W1532914794 @default.
- W4322005966 hasRelatedWork W1560866723 @default.
- W4322005966 hasRelatedWork W1566605096 @default.
- W4322005966 hasRelatedWork W1822375475 @default.
- W4322005966 hasRelatedWork W2009755506 @default.
- W4322005966 hasRelatedWork W2184406576 @default.
- W4322005966 hasRelatedWork W2354373235 @default.
- W4322005966 hasRelatedWork W2367384407 @default.
- W4322005966 hasRelatedWork W2983867517 @default.
- W4322005966 hasRelatedWork W4297973245 @default.
- W4322005966 isParatext "false" @default.
- W4322005966 isRetracted "false" @default.
- W4322005966 workType "article" @default.