Title :
Systolic architectures for Hopfield network, BAM and multi-layer feed-forward network
Author_Institution :
Dept. of Electr. Eng., Windsor Univ., Ont., Canada
Abstract :
The systolic array architectures of a number of well-known artificial neural networks are presented. The artificial neural networks considered include the Hopfield neural network, bidirectional associative memories, and the multilayer feedforward neural network. The architectures presented are regular and are designed to operate in pipelined fashion
Keywords :
cellular arrays; content-addressable storage; neural nets; parallel architectures; pipeline processing; Hopfield neural network; artificial neural networks; bidirectional associative memories; multilayer feedforward neural network; pipelined fashion operation design; regular architectures; systolic array architectures; Artificial neural networks; Associative memory; Feedforward neural networks; Feedforward systems; Hopfield neural networks; Magnesium compounds; Multi-layer neural network; Neural networks; Neurons; Systolic arrays;
Conference_Titel :
Circuits and Systems, 1989., IEEE International Symposium on
Conference_Location :
Portland, OR
DOI :
10.1109/ISCAS.1989.100469
