Zobrazeno 1 - 7
of 7
pro vyhledávání: '"Ramin Shaghaghi Kandovan"'
Autor:
Maryam Asgharnia, S. Abolfazl Hosseini, Ali Shahzadi, Saeed Ghazi-Maghrebi, Ramin Shaghaghi Kandovan
Publikováno v:
IEEE Access, Vol 12, Pp 148916-148934 (2024)
Universal Filtered Multi-Carrier (UFMC) is a new multi-carrier system regarded as a candidate for future wireless communication systems. This paper investigates the application of the UFMC technique in Multiple Input-Multiple Output communications (M
Externí odkaz:
https://doaj.org/article/df1f9ce5bc304c7ab44623a671f2d285
Publikováno v:
IEEE Access, Vol 1, Pp 404-407 (2013)
This paper suggests a real-valued sparse representation method using a unitary transformation that can convert complex-valued manifold matrices from uniform circular array into real ones. Because of this transformation, the computational complexity i
Externí odkaz:
https://doaj.org/article/b1f30418160440bf88194b227663269c
Publikováno v:
Peer-to-Peer Networking and Applications. 15:1328-1344
Publikováno v:
The Computer Journal. 66:229-244
Mobile edge computing (MEC) is a key feature of next-generation heterogeneous networks aimed at providing a variety of services for different applications by performing related processing tasks closer to the user equipment. In this research, we inves
Publikováno v:
Advances in Remote Sensing. :66-75
One of the most challenges in the remote sensing applications is Hyperspectral image classification. Hyperspectral image classification accuracy depends on the number of classes, training samples and features space dimension. The classification perfo
Publikováno v:
2017 IEEE 13th Malaysia International Conference on Communications (MICC).
Relay selection and network coding are two main factors for improving cooperative Networks. Employing all the relays without any relay selection in the network increase power consumption and cost to transfer data. Selection of one or more relays decr
Publikováno v:
CSO (1)
In this paper Persian language verification system is proposed and evaluated. This technique is constructed by using Gaussian mixture models as a basic system for tokenizing and a Neural Network as the backend processor. Performances result are prese