Title :
Defect tolerant implementations of feed-forward and recurrent neural networks
Author :
Franzon, Paul ; Van den Bout, David ; Paulos, John ; Miller, Thomas, III ; Snyder, Wesley ; Nagle, Troy ; Liu, Wentai
Author_Institution :
Dept. of Electr. & Comput. Eng., North Carolina State Univ., Raleigh, NC, USA
Abstract :
Many of the defect tolerant techniques employed to achieve wafer-scale integration can also be used to construct flexible and scalable architectures. These techniques are applied to two artificial neural networks: a feed-forward analog network with backpropagation and an efficient digital recurrent network
Keywords :
VLSI; computer architecture; digital integrated circuits; fault tolerant computing; integrated circuit technology; neural nets; WSI; artificial neural networks; backpropagation; defect tolerant implementations; defect tolerant techniques; digital recurrent network; feed-forward analog network; feed-forward neural networks; recurrent neural networks; scalable architectures; wafer-scale integration; Artificial neural networks; Computer architecture; Feedforward neural networks; Feedforward systems; Feeds; Large-scale systems; Neural networks; Neurons; Recurrent neural networks; Wafer scale integration;
Conference_Titel :
Wafer Scale Integration, 1990. Proceedings., [2nd] International Conference on
Conference_Location :
San Francisco, CA
Print_ISBN :
0-8186-9013-5
DOI :
10.1109/ICWSI.1990.63897
