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DATE
2008
IEEE

Scalable Architecture for on-Chip Neural Network Training using Swarm Intelligence

10 years 11 months ago
Scalable Architecture for on-Chip Neural Network Training using Swarm Intelligence
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 are sequentially mapped to available functional units. Thus, the architecture is reconfigurable for training and implementing different multilayer feedforward neural networks without the need for modifying the architecture. The implementation is intended for real-time applications regarding hardware cost and speed. The results show that the proposed system provides a trade-off between resource requirements and speed.
Amin Farmahini Farahani, Seid Mehdi Fakhraie, Saee
Added 29 May 2010
Updated 29 May 2010
Type Conference
Year 2008
Where DATE
Authors Amin Farmahini Farahani, Seid Mehdi Fakhraie, Saeed Safari
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