Synchronization of Interacting Neural Networks
Tian Yon · World Sci-tech R & D · 2013
Several scenarios of interacting neural networks especially Tree Parity Machine are widely used in many fields such as cryptography.This kind of neural networks has some good properties such as they can reach a same state by transmitting some information limited.In this paper,the synchronization patterns of Tree Parity Machines are discussed,named leam-neighbor pattern and distributed pattern.Based on the schemes of the two patterns,the advantages of the patterns are investigated,as well as the differences and relations.The experimental results show that the distributed pattern is better than the learn-neighbor pattern on the time complexity and the system architecture is simple.