Design and Implementation of Neural Networks Neurons with RadBas, LogSig, and TanSig Activation Functions on FPGA
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Dosyalar
Tarih
2012
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Kaunas Univ Technology
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
I. Sahin, I. Koyuncu. Design and Implementation of Neural Networks Neurons with RadBas, LogSig, and TanSig Activation Functions on FPGA // Electronics and Electrical Engineering. - Kaunas: Technologija, 2012. - No. 4(120). - P. 51-54. Artificial Neural Networks (ANNs) are utilized in several key areas such as prediction, classification, motor control, etc. When high performance is needed, FPGA realizations of the ANNs are preferred. In this study, we designed and implemented a total of 18 different FPGA-based neurons, 2, 4 and 6-input biased and non-biased with each having three different activation functions requiring the calculations of e(x). Our purpose was to show the possibility of implementing neural networks with exponential activation functions on current FPGAs and measure the performance of the neurons. The results showed that up to 10 neurons can fit in to the smallest Virtex-6 and the network can be clocked up to 405MHz. Ill. 6, bibl. 11, tabl. 2 (in English; abstracts in English and Lithuanian).
Açıklama
WOS: 000303226800011
Anahtar Kelimeler
Kaynak
Elektronika Ir Elektrotechnika
WoS Q Değeri
Q4
Scopus Q Değeri
Q3
Cilt
120
Sayı
4