FPGA Architecture Comparison for Non-Conventional Signal Processing

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IEEE-INNS-ENNS International Joint Conference on Neural Networks (IJCNN'00)-Volume 2

Como, Italy

July 24-July 27

ISBN: 0-7695-0619-4

	ASCII Text	x
	D. Franco, L. Carro, "FPGA Architecture Comparison for Non-Conventional Signal Processing," Neural Networks, IEEE - INNS - ENNS International Joint Conference on, vol. 2, pp. 2055, IEEE-INNS-ENNS International Joint Conference on Neural Networks (IJCNN'00)-Volume 2, 2000.

	BibTex	x
	@article{ 10.1109/IJCNN.2000.857874, author = {D. Franco and L. Carro}, title = {FPGA Architecture Comparison for Non-Conventional Signal Processing}, journal ={Neural Networks, IEEE - INNS - ENNS International Joint Conference on}, volume = {2}, year = {2000}, issn = {1098-7576}, pages = {2055}, doi = {http://doi.ieeecomputersociety.org/10.1109/IJCNN.2000.857874}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, }

	RefWorks Procite/RefMan/Endnote	x
	TY - CONF JO - Neural Networks, IEEE - INNS - ENNS International Joint Conference on TI - FPGA Architecture Comparison for Non-Conventional Signal Processing SN - 1098-7576 SP EP A1 - D. Franco, A1 - L. Carro, PY - 2000 VL - 2 JA - Neural Networks, IEEE - INNS - ENNS International Joint Conference on ER -

D. Franco, Universidade Federal do Rio Grande do Sul

L. Carro, Universidade Federal do Rio Grande do Sul

DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/IJCNN.2000.857874

In the design of a specific application requiring scalar processing and a neural network, it was noticed that the same underlying hardware used to process analog signals could be used as another way to implement neural networks. This paper presents the main ideas behind this design approach, and a comparison in terms of area and processing speeds of both solutions, when using an FPGA as a substrate.

Citation:

D. Franco, L. Carro, "FPGA Architecture Comparison for Non-Conventional Signal Processing," ijcnn, vol. 2, pp.2055, IEEE-INNS-ENNS International Joint Conference on Neural Networks (IJCNN'00)-Volume 2, 2000

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