ABSTRACT A large number of VLSI implementationsof neural networkmodels have been reported. The diversityof these implementations is noteworthy. This paper attempts to put a group of representative VLSI implementations in perspective by comparing and contrasting them. IMPLEMENTATION Changing the way information is represented can be beneficial. For examplea change of representation can make information more compact for storage and transmission.

ABSTRACT A large number of VLSI implementations of neural network models have been reported. The diversity of these implementations is noteworthy. This paper attempts to put a group of representative VLSI implementations in perspective by comparing and contrasting them. Design tradeoffs are discussed and some suggestions forthe direction of future implementation efforts are made. IMPLEMENTATION Changing the way information is represented can be beneficial.