Zobrazeno 1 - 10
of 58
pro vyhledávání: '"Andjela Draganic"'
Publikováno v:
IEEE Access, Vol 12, Pp 116226-116237 (2024)
Probability estimation measures the likelihood of different outcomes in a statistical context. It commonly involves estimating either the parameters or the entire distribution of a random variable. Parametric approaches, where a specific functional f
Externí odkaz:
https://doaj.org/article/acff69297ef44a0da50eb53cef7c566d
Publikováno v:
SSRN Electronic Journal.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::717a675ae2a054d074d34e527aee310e
https://doi.org/10.2139/ssrn.4237481
https://doi.org/10.2139/ssrn.4237481
Autor:
Zhiqiang Zhu, Ruiqin Ma, Andjela Draganic, Jingjie Wang, Xiaoshuan Zhang, Xiang Wang, Irena Orovic
Publikováno v:
Journal of Food Process Engineering. 45
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3677c9bba5031b06986aa3ce49359a1b
https://doi.org/10.1111/jfpe.13918
https://doi.org/10.1111/jfpe.13918
Publikováno v:
SoftCOM
The paper analyses the reconstruction accuracy of the under-sampled seismic signals. Several different types of seismic signals are observed. The signals are non-uniformly sampled, according to the requirement of the Compressive Sensing approach. Dif
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d43c7729e74361ce969a19518c71c7b6
https://doi.org/10.23919/softcom52868.2021.9559132
https://doi.org/10.23919/softcom52868.2021.9559132
Publikováno v:
MECO
The quick response code has been used in many applications nowadays. In this work, we examined the encoding performance when code image is highly under-sampled. The random under-sampling process is considered and motivated by the Compressive Sensing
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d4f3140cf281c415dcc6fc05c290f32a
https://doi.org/10.1109/meco49872.2020.9134345
https://doi.org/10.1109/meco49872.2020.9134345
Publikováno v:
Telfor Journal, Vol 9, Iss 2, Pp 92-97 (2017)
Signal sparsity is exploited in various signal processing approaches. Signal compression, classification, coding, as well as the recently introduced compressed sensing are some examples where the possibility to represent a signal sparsely determines
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::cf6f9f0311a57a8139eb1fcc49f9eed3
https://doaj.org/article/4db7642d032d42eda20892a33120dc97
https://doaj.org/article/4db7642d032d42eda20892a33120dc97
Publikováno v:
Microprocessors and Microsystems. 51:106-113
Classification of interfering signals that belong to different wireless standards is important topic in wireless communications. In this paper, we propose a procedure for separation and classification of wireless signals belonging to the Bluetooth an
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e9f8462f2546afdb97c006f8ecf79b15
https://doi.org/10.1016/j.micpro.2017.04.010
https://doi.org/10.1016/j.micpro.2017.04.010
Publikováno v:
Facta universitatis - series: Electronics and Energetics. 30:477-510
Compressive Sensing, as an emerging technique in signal processing is reviewed in this paper together with its common applications. As an alternative to the traditional signal sampling, Compressive Sensing allows a new acquisition strategy with signi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ed557ac3cd3569108703954c78cc27a1
https://doi.org/10.2298/fuee1704477d
https://doi.org/10.2298/fuee1704477d
Publikováno v:
IET Radar, Sonar & Navigation. 9:1260-1267
Time–frequency (TF) distributions have been used for providing high-resolution representation in a large number of signal processing applications. However, high resolution and accurate instantaneous frequency (IF) estimation usually depends on the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a9a1804bb60be613c892f9e0da1f5c24
https://doi.org/10.1049/iet-rsn.2015.0116
https://doi.org/10.1049/iet-rsn.2015.0116
Autor:
Maja Lakičević Žarić, Stefan Vujovic, Srdjan Stankovic, Andjela Draganic, Irena Orovic, Milos Dakovic, Marko Beko
Publikováno v:
Sensors (Basel, Switzerland)
Sensors, Vol 20, Iss 2602, p 2602 (2020)
Sensors
Volume 20
Issue 9
Sensors, Vol 20, Iss 2602, p 2602 (2020)
Sensors
Volume 20
Issue 9
The virtual (software) instrument with a statistical analyzer for testing algorithms for biomedical signals&rsquo
recovery in compressive sensing (CS) scenario is presented. Various CS reconstruction algorithms are implemented with the aim to be
recovery in compressive sensing (CS) scenario is presented. Various CS reconstruction algorithms are implemented with the aim to be
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::20396d8f89bfa2445c3ee93e656f26ec
https://doi.org/10.3390/s20092602
https://doi.org/10.3390/s20092602