relaxation network, probabilistic connections, input persistence, activation function
This paper reports results from studying the behavior of Hopfield-type networks with probabilistic connections. As the probabilities decrease, network performance degrades. In order to compensate, two network modifications - input persistence and a new activation function - are suggested, and empirical results indicate that the modifications significantly improve network performance.
Original Publication Citation
Dan Ventura, "Probabilistic Connections in Relaxation Networks", Proceedings of the International Joint Conference on Neural Networks, pp.934-938, May 22.
BYU ScholarsArchive Citation
Ventura, Dan A., "Probabilistic Connections in Relaxation Networks" (2002). Faculty Publications. 543.
Physical and Mathematical Sciences
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