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001-es BibID:	BIBFORM032861
035-os BibID:	WOS:000291967300149
Első szerző:	Oniga István László (villamosmérnök)
Cím:	Adaptive Hardware-Software Co-Design Platform for Fast Prototyping of Embedded Systems / Stefan Oniga, Alin Tisan, Claudiu Lung, Attila Buchman, Ioan Orha
Dátum:	2010
ISSN:	1842-0133
Megjegyzések:	This paper presents the hardware-software co-design platform based onFPGA developed for fast prototyping of embedded systems using hardwaremodules that can be easily connected and "driver" modules that canmanage I/O devices and sensors basic behavior. Having this framework,adding of a new I/O peripheral needs only design and synthesis of anapplication specific VHDL or software module. Using neural networks (NN)to add learning capabilities and adaptive behavior is essential for anintelligent system and the use of FPGA is an important feature in termsof their hardware implementation. The designed architecture allows theinsertion of intelligent interface based on neural networks created withthis type of modules. This platform is based on low cost general purposeFPGA boards without need for hardware design.
Tárgyszavak:	Műszaki tudományok Villamosmérnöki tudományok konferenciacikk Adaptive behavior Fast prototyping FPGA boards Hardware implementations Hardware software codesign I/O Device Intelligent interface Learning capabilities Software modules
Megjelenés:	12th International Conference on Optimization of Electrical and Electronic Equipment, OPTIM 2010. - (2010), p. 1004-1009. -
További szerzők:	Tisan, Alin Lung, Claudiu (1977-) (villamosmérnök) Buchman Attila (1957-) (villamosmérnök) Orha, Ioan
Internet cím:	Intézményi repozitóriumban (DEA) tárolt változat DOI
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001-es BibID:	BIBFORM027884
Első szerző:	Oniga István László (villamosmérnök)
Cím:	FPGA implementation of feed-forward neural networks for smart devices development / Stefan Oniga, Alin Tisan, Daniel Mic, Claudiu Lung, Ioan Orha, Attila Buchman, Andrei Vida-Ratiu
Dátum:	2009
Megjegyzések:	This paper presents the results obtained in the implementation of Feed-Forward Artificial Neural Networks (FFANN) with one or several layers, used in the development of smart devices that needs learning capability and adaptive behavior. The networks were implemented using ANN specific blocks created by the authors using the System Generator software. The training and the testing of the networks was conducted using sets of 150 training and test vectors with 7 elements. 2009 IEEE.
Tárgyszavak:	Műszaki tudományok Villamosmérnöki tudományok konferenciacikk Adaptive behavior Feed-forward artificial neural networks FPGA implementations Learning capabilities Smart devices
Megjelenés:	International Symposium on Signals, Circuits and Systems ISSCS 2009, Iasi, Romania, 9-10 July 2009. - (2009), p. 401-404. -
További szerzők:	Tisan, Alin Mic, Daniel Lung, Claudiu (1977-) (villamosmérnök) Orha, Ioan Buchman Attila (1957-) (villamosmérnök) Vida-Ratiu, Andrei
Internet cím:	Szerző által megadott URL DOI Intézményi repozitóriumban (DEA) tárolt változat
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