Title :
Systolic implementation of neural networks
Author :
Zubair, M. ; Madan, B.B.
Author_Institution :
Dept. of Comput. Sci., Old Dominion Univ., Norfolk, VA, USA
Abstract :
Systolic implementation of neural networks is suggested. These arrays do not suffer from long feedback connections. Various learning rules are incorporated in the suggested systolic implementation of neural networks. It is shown that these arrays can be easily generalized for multilayered feedforward networks
Keywords :
neural nets; parallel architectures; arrays; learning rules; multilayered feedforward networks; neural networks; systolic implementation; Computational modeling; Computer networks; Feedforward neural networks; Hopfield neural networks; Multi-layer neural network; Neural networks; Neurofeedback; Neurons; Optical computing; Optical feedback;
Conference_Titel :
Computer Design: VLSI in Computers and Processors, 1989. ICCD '89. Proceedings., 1989 IEEE International Conference on
Conference_Location :
Cambridge, MA
Print_ISBN :
0-8186-1971-6
DOI :
10.1109/ICCD.1989.63412
