Pregled bibliografske jedinice broj: 1268851
Local Shannon, Rényi, and Tsallis Entropy for Useful Content Extraction from Choi-Williams and Zhao-Atlas-Marks Time-Frequency Distributions
Local Shannon, Rényi, and Tsallis Entropy for Useful Content Extraction from Choi-Williams and Zhao-Atlas-Marks Time-Frequency Distributions // 2022 International Conference on Electrical, Computer, Communications and Mechatronics Engineering (ICECCME)
Malé, Maldivi: Institute of Electrical and Electronics Engineers (IEEE), 2022. str. 1-5 doi:10.1109/iceccme55909.2022.9988560 (predavanje, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)
CROSBI ID: 1268851 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
Local Shannon, Rényi, and Tsallis Entropy for
Useful Content Extraction from Choi-Williams and
Zhao-Atlas-Marks Time-Frequency Distributions
Autori
Lackovic, Ana Vrankovic ; Lerga, Jonatan ; Tomic, Marijana
Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni
Skup
2022 International Conference on Electrical, Computer, Communications and Mechatronics Engineering (ICECCME)
Mjesto i datum
Malé, Maldivi, 16.11.2022. - 18.11.2022
Vrsta sudjelovanja
Predavanje
Vrsta recenzije
Međunarodna recenzija
Ključne riječi
Renyi’s entropy, Shannon entropy, Tsallis entropy, Time-frequency distributions, Useful content extraction
Sažetak
In this paper, we extend the research study on the 2D local entropy method (2DLEM) by applying new entropy measures and time-frequency distributions. In our earlier work, 2D local entropy method is introduced and implemented to the test using both a small sample of real-world data and synthetic signals. We now broaden the scope of our method by applying it to time-frequency distributions that were not introduced in the original paper, as well as changing the entropy measure that is used within the method. Results show that for linear and separate component signals, non-parameterized Shannon entropy is a better choice, while the distributions that were used in the original study outperformed the others.
Izvorni jezik
Engleski
Znanstvena područja
Računarstvo
POVEZANOST RADA
Projekti:
EK--951732 - Nacionalni centri kompetencija u okviru EuroHPC (EUROCC) (Štula, Maja; Kranjčević, Lado; Kovač, Mario; Skala, Karolj; Miletić, Vedran, EK ) ( CroRIS)
MINGO-ESIF-KK.01.2.1.02.0179 - ABsistemDCiCloud (ABsistemDCiCloud) (Lerga, Jonatan, MINGO - Fond: Europski fond za regionalni razvoj Program: OP Konkurentnost i kohezija 2014. - 2020. Jačanje gospodarstva primjenom istraživanja i inovacija Područje: IRI - Povećanje razvoja novih proizvoda i usluga koji proizlaze iz aktivnosti istraživanja i raz) ( CroRIS)
MZO-BI-HR/20-21-043 - Analiza hiperspektralnih slika korištenjem strojnog učenja i adaptivnog filtrianja prilagođenog podacima (Lerga, Jonatan, MZO ) ( CroRIS)
VLASTITA-SREDSTVA-uniri-tehnic-17 - Računalom potpomognuta digitalna analiza i klasifikacija signala (UNIRI-TEHNIC-18-17) (Lerga, Jonatan, VLASTITA-SREDSTVA - UNIRI2018) ( CroRIS)
Ustanove:
Tehnički fakultet, Rijeka,
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