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Proceedings of the conference on Design, automation and test in Europe - DATE '08
This paper presents a novel architecture for on-chip neural network training using particle swarm optimization (PSO). PSO is an evolutionary optimization algorithm with a growing field of applications which has been recently used to train neural networks. The architecture exploits PSO algorithm to evolve network weights as well as a method called layer partitioning to implement neural networks. In the proposed method, a neural network is partitioned into groups of neurons and the groups aredoi:10.1145/1403375.1403698 fatcat:zgn2q3fdnzf2pbsdd6l45mq5dm