Találati lista | Tudóstér

001-es BibID:	BIBFORM032870
035-os BibID:	WOS:000255232500020
Első szerző:	Gavrincea, Ciprian
Cím:	Survey of wavelet based denoising filter design / G. C. Gavrincea, A. Tisan, A. Buchman, S. Oniga
Dátum:	2007
Megjegyzések:	This paper presents theoretical and practical aspects in conjunctionwith hardware implementation of wavelet based denoising filters. Thewavelets can tackle the denoising problem optimally from the point ofview that the wavelet based denoising attempts to remove whatever noiseis present and retain whatever signal is present regardless to thefrequency content of the signal. In the field of designing signalprocessing systems, "time to market" represents a key factor. Hardwareimplementation using field programmable gate arrays (FPGA) can reducetime to market for signal processing systems. The paper analyzes andcompares different solution for hardware implementation of wavelet baseddenoising filters using FPGAs.
Tárgyszavak:	Műszaki tudományok Villamosmérnöki tudományok konferenciacikk
Megjelenés:	30th International Spring Seminar on Electronics Technology : Emerging Technologies for Electronics Packaging : May 9-13, 2007, Cluj-Napoca, Romania : conference proceedings. - (2007), p. 112-116. -
További szerzők:	Tisan, Alin Buchman Attila (1957-) (villamosmérnök) Oniga István László (1960-) (villamosmérnök)
Internet cím:	DOI Intézményi repozitóriumban (DEA) tárolt változat
Borító:
Saját polcon:

001-es BibID:	BIBFORM032873
035-os BibID:	WOS:000255232500111
Első szerző:	Tisan, Alin
Cím:	A generic control block for feedforward neural network with on-chipdelta rule learning algorithm / Alin Tisan, A. Buchman, Ş. Oniga, C. Gavrincea
Dátum:	2007
Megjegyzések:	In this paper we propose a method to implement in FPGA a feedforwardneural network with on-chip delta rule learning algorithm. For this, wehave develop a generic blocks designed in Mathworks' Simulinkenvironment, capable to generate the signals for controlling the neuronsfrom a neural network. The main characteristics of those blocks is itshigh reconfigurability that's makes it suitable for developing of ageneric controlling block capable to manage calculus function of neuronsfrom different layers. The properties of the block are set according tothe numbers of total layers, number of the neurons from the layers andthe number of layer from whom and in different Function Block Parameterswindows. The novelty of the proposed method resides in the possibilityto design neural networks with on-chip learning only with predefinedblock systems created in System Generator environment. The major benefitof this design methodology result from the possibility to create ahigher level design tools used to implement neural networks in logicalcircuits.
Tárgyszavak:	Műszaki tudományok Villamosmérnöki tudományok konferenciacikk
Megjelenés:	30th International Spring Seminar on Electronics Technology : Emerging Technologies for Electronics Packaging : May 9-13, 2007, Cluj-Napoca, Romania : conference proceedings. - (2007), p. 567-570. -
További szerzők:	Buchman Attila (1957-) (villamosmérnök) Oniga István László (1960-) (villamosmérnök) Gavrincea, Ciprian
Internet cím:	DOI Intézményi repozitóriumban (DEA) tárolt változat
Borító:
Saját polcon:

001-es BibID:	BIBFORM032869
035-os BibID:	WOS:000250471700067
Első szerző:	Tisan, Alin
Cím:	Architecture and algorithms for syntetizable neural networks withon-chip learning / Alin Tisan, Ştefan Oniga, Buchman Attila, Gavrincea Ciprian
Dátum:	2007
Megjegyzések:	This paper presents a synthesizable programmable logic blocksarchitectures, describes the associated formula that makes the blocks tobe generic for a backpropagation neural network (NN) with on-chip deltarule learning. The architecture proposed herein takes advantage ofdistinct datapaths for the forward and backward propagation stages tosignificantly improve the performance of the learning phase. Thearchitecture is easily scalable and able to cope with arbitrary networksizes with the same hardware.
Tárgyszavak:	Műszaki tudományok Villamosmérnöki tudományok konferenciacikk
Megjelenés:	International Symposium on Signals, Circuits, and Systems : July 12-13, 2007, Iasi, Romania : proceedings. -
További szerzők:	Oniga István László (1960-) (villamosmérnök) Buchman Attila (1957-) (villamosmérnök) Gavrincea, Ciprian
Internet cím:	Intézményi repozitóriumban (DEA) tárolt változat DOI
Borító:
Saját polcon:

001-es BibID:	BIBFORM032868
035-os BibID:	WOS:000258474700015
Első szerző:	Tisan, Alin
Cím:	FPGA implementation of a self-organized map with on-chip learning / A. Tisan, S. Oniga, C. Gavrincea, A. Buchman
Dátum:	2008
Megjegyzések:	In this paper we propose a method to implement SOM neural network inFPGA circuits: a self organized map neural network with on-chip learningalgorithm. The method implies the building of a neural network bygeneric blocks designed in Mathworks' Simulink environment. The maincharacteristics of this solution are on-chip learning algorithmimplementation and high reconfiguration capability and operation underreal time constraints.
Tárgyszavak:	Műszaki tudományok Villamosmérnöki tudományok konferenciacikk
Megjelenés:	International Conference on Optimization of Electrical and Electronic Equipment (11.)(2008)(Brașov, Romania). - 11th International Conference on Optimization of Electrical and Electronic Equipment. - (2008), p. 81-86. -
További szerzők:	Oniga István László (1960-) (villamosmérnök) Gavrincea, Ciprian Buchman Attila (1957-) (villamosmérnök)
Internet cím:	Intézményi repozitóriumban (DEA) tárolt változat DOI
Borító:
Saját polcon: