메뉴 건너뛰기




Volumn 2, Issue , 2010, Pages 258-264

A single layer architecture to FPGA implementation of BP artificial neural network

Author keywords

Architecture; FPGA; Hardware implementation; Neural network

Indexed keywords

ARTIFICIAL NEURAL NETWORK; BACK-PROPAGATION ARTIFICIAL NEURAL NETWORK; BP ARTIFICIAL NEURAL NETWORK; CARBON FIBRES; DEFECTS CLASSIFICATION; FPGA; FPGA IMPLEMENTATIONS; FPGA-HARDWARE IMPLEMENTATION; HARDWARE IMPLEMENTATION; HARDWARE IMPLEMENTATIONS; NON-DESTRUCTION; SINGLE LAYER;

EID: 77953052752     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CAR.2010.5456553     Document Type: Conference Paper
Times cited : (6)

References (22)
  • 1
    • 34248645728 scopus 로고    scopus 로고
    • Feedforward neural network implementation in FPGA using layer multiplexing for effective resource utilization
    • May
    • S. Himavathi, D. Anitha, and A. Muthuramalingam, "Feedforward neural network implementation in FPGA using layer multiplexing for effective resource utilization," IEEE Transactions on neural networks, Vol. 18, NO.3, May 2007, pp: 880-888.
    • (2007) IEEE Transactions on Neural Networks , vol.18 , Issue.3 , pp. 880-888
    • Himavathi, S.1    Anitha, D.2    Muthuramalingam, A.3
  • 6
    • 0033322982 scopus 로고    scopus 로고
    • Towards an FPGA based reconfigurable computing environment for neural network implementations
    • Sep
    • J. Zhu, G. J. Milne, and B. K. Gunther, "Towards an FPGA based reconfigurable computing environment for neural network implementations," Inst. Elect. Eng. Proc. Artif. Neural Netw., vol. 2, no. 470,Sep. 1999,pp. 661-666.
    • (1999) Inst. Elect. Eng. Proc. Artif. Neural Netw. , vol.2 , Issue.470 , pp. 661-666
    • Zhu, J.1    Milne, G.J.2    Gunther, B.K.3
  • 7
    • 6344229354 scopus 로고    scopus 로고
    • Highly efficient limited range multipliers for LUT-based FPGA architectures
    • Oct
    • R. H. Turner and R. F. Woods, "Highly efficient limited range multipliers for LUT-based FPGA architectures," IEEE Trans. Very Large Scale Integr. (VLSI) Syst., vol. 15, no. 10, Oct. 2004, pp. 1113-1117.
    • (2004) IEEE Trans. Very Large Scale Integr. (VLSI) Syst. , vol.15 , Issue.10 , pp. 1113-1117
    • Turner, R.H.1    Woods, R.F.2
  • 10
    • 0032265783 scopus 로고    scopus 로고
    • FPGA implementation of a multilayer preceptron neural network using VHDL
    • Y. Taright and M. Hubin, "FPGA implementation of a multilayer preceptron neural network using VHDL," Proc. Int. Conf. Signal Process. (ICSP), vol. 2, 1998, pp. 1306-1310.
    • (1998) Proc. Int. Conf. Signal Process. (ICSP) , vol.2 , pp. 1306-1310
    • Taright, Y.1    Hubin, M.2
  • 11
    • 34248672477 scopus 로고    scopus 로고
    • Hardware implementation of neural network on FPGA for accidents diagnosis of the multi-purpose reactor of Egypt
    • Dec.
    • M. M. Syiam, H. M. Klash, I. I. Mahmoud, and S. S. Haggag, "Hardware implementation of neural network on FPGA for accidents diagnosis of the multi-purpose reactor of Egypt," in Proc. 15th Int. Conf. Microelectron. (ICM), Dec. 2003, pp. 326-329.
    • (2003) Proc. 15th Int. Conf. Microelectron. (ICM) , pp. 326-329
    • Syiam, M.M.1    Klash, H.M.2    Mahmoud, I.I.3    Haggag, S.S.4
  • 13
    • 0026838206 scopus 로고
    • GANGLION- A Fast Field- Programmable Gate Array Implementation of a Connectionist Classifier
    • C.E. Cox, W.E. Blanz, "GANGLION- A Fast Field- Programmable Gate Array Implementation of a Connectionist Classifier", Journal of Solid State Circuits, 1992, 27 (3): 288-299.
    • (1992) Journal of Solid State Circuits , vol.27 , Issue.3 , pp. 288-299
    • Cox, C.E.1    Blanz, W.E.2
  • 15
    • 33750201788 scopus 로고    scopus 로고
    • Hardware implementation of multilayer feed forward network with intelligent neuron
    • Z Haiyan, L Xin, Hardware implementation of multilayer feed forward network with intelligent neuron, Journal of Harbin Engineering University, 2006, 27: 40-45.
    • (2006) Journal of Harbin Engineering University , vol.27 , pp. 40-45
    • Haiyan, Z.1    Xin, L.2
  • 19
    • 23044500767 scopus 로고    scopus 로고
    • Study on denoising techniques for ultrasonic signals in wavelet domain based on neural networks
    • Y. Keji, Study on denoising techniques for ultrasonic signals in wavelet domain based on neural networks, Journal of Zhejiang University (Engineering Science), 2005,39 (6): 775-779.
    • (2005) Journal of Zhejiang University (Engineering Science) , vol.39 , Issue.6 , pp. 775-779
    • Keji, Y.1
  • 20
    • 34248640484 scopus 로고
    • Multilayer feedforward neural networks are universal approximators
    • K. M. Hornick, M. Stinchcombe, and H. white, "Multilayer feedforward neural networks are universal approximators," Neural Netw., vol. 2, no. 5, pp. 141-154, 1985.
    • (1985) Neural Netw , vol.2 , Issue.5 , pp. 141-154
    • Hornick, K.M.1    Stinchcombe, M.2    White, H.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.