Zobrazeno 1 - 10
of 20
pro vyhledávání: '"Hamid Reza Mahdiani"'
Publikováno v:
IEEE Transactions on Neural Systems and Rehabilitation Engineering, Vol 30, Pp 2896-2905 (2022)
Independent Component Analysis (ICA) is a common method exploited in different biomedical signal processing applications, especially in noise removal of electroencephalography (EEG) signals. Among different existing ICA algorithms, FastICA is a popul
Externí odkaz:
https://doaj.org/article/fd81f951969e45799e07f448705a993a
Publikováno v:
Engineering Science and Technology, an International Journal, Vol 23, Iss 2, Pp 289-298 (2020)
Emerging nano-level technologies provide very high device densities that facilitate high performance implementation of more complex applications. However, they also introduce new challenging reliability issues such as appearance of transient faults a
Externí odkaz:
https://doaj.org/article/18dd0b39876b42c88a821880c9ab2374
Publikováno v:
Journal of Forecasting. 42:101-123
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9b671f20c28c7429ea05befa7f61f4ae
https://doi.org/10.1002/for.2889
https://doi.org/10.1002/for.2889
Autor:
Hamid Reza Mahdiani
Publikováno v:
The Journal of Supercomputing. 78:7768-7787
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::42a7ab5e6c6031eb8794f17521b37cd9
https://doi.org/10.1007/s11227-021-04167-8
https://doi.org/10.1007/s11227-021-04167-8
Publikováno v:
IEEE Transactions on Neural Systems and Rehabilitation Engineering. 30:2896-2905
Independent Component Analysis (ICA) is a common method exploited in different biomedical signal processing applications, especially in noise removal of electroencephalography (EEG) signals. Among different existing ICA algorithms, FastICA is a popul
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4a67846f503e8fd75d0a790855909f6b
https://doi.org/10.1109/tnsre.2022.3213010
https://doi.org/10.1109/tnsre.2022.3213010
Publikováno v:
IEEE Transactions on Computers. 69:1376-1387
Due to considerable effectiveness of the imprecise computing paradigm in hardware implementation of many applications, great attention has been recently paid by many research groups to develop different novel imprecise computational blocks such as ad
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4ff77958eb80376087fc5531e5543989
https://doi.org/10.1109/tc.2020.2972549
https://doi.org/10.1109/tc.2020.2972549
Publikováno v:
IEEE Transactions on Circuits and Systems I: Regular Papers. 67:1912-1924
Eigenvalue Decomposition (EVD) and Singular Value Decomposition (SVD) are two crucial transformations in many signal processing applications. The main drawback of these algorithms is their computationally intensive nature which prevents them to be ef
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e933db0b7fa744538952f5aa9bafaaab
https://doi.org/10.1109/tcsi.2020.2973249
https://doi.org/10.1109/tcsi.2020.2973249
Publikováno v:
Engineering Science and Technology, an International Journal, Vol 23, Iss 2, Pp 289-298 (2020)
Emerging nano-level technologies provide very high device densities that facilitate high performance implementation of more complex applications. However, they also introduce new challenging reliability issues such as appearance of transient faults a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::448a0dccb6dc34ef2985f680ea7d8965
http://www.sciencedirect.com/science/article/pii/S2215098618322195
http://www.sciencedirect.com/science/article/pii/S2215098618322195
Publikováno v:
Soft Computing. 24:4991-5004
Nowadays, with the emergence of new technologies such as smart grid and increasing the use of renewable energy in the grid, energy prediction has become more important in the electricity industry. Furthermore, with growing the integration of power ge
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::96e65e944c0798d7875d336a79c5ed7e
https://doi.org/10.1007/s00500-019-04249-z
https://doi.org/10.1007/s00500-019-04249-z
Publikováno v:
2020 20th International Symposium on Computer Architecture and Digital Systems (CADS).
Canonical Correlation Analysis is widely exploited in different signal processing applications such as detection of the brain internal activity in an SSVEP based Brain-Computer Interface system. The main disadvantage of the CCA algorithm is its compu
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8deec5fd71f475afb3690a4709044706
https://doi.org/10.1109/cads50570.2020.9211863
https://doi.org/10.1109/cads50570.2020.9211863