A Modified Hopfield Model for Solving the N-Queens Problem
IJCNN '00 Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks (IJCNN'00)-Volume 6 - Volume 6
Primal and dual assignment networks
IEEE Transactions on Neural Networks
“Optimal” Hopfield network for combinatorial optimization with linear cost function
IEEE Transactions on Neural Networks
The hysteretic Hopfield neural network
IEEE Transactions on Neural Networks
A generalized control-flow-aware pattern recognition algorithm for behavioral synthesis
Proceedings of the Conference on Design, Automation and Test in Europe
Hi-index | 0.00 |
In the use of Hopfield networks to solve optimization problems, a critical problem is the determination of appropriate values of the parameters in the energy function so that the network can converge to the best valid solution. In this paper, we first investigate the relationship between the parameters in a typical class of energy functions, and consequently propose a "guided trial-and-error" technique to determine the parameter values. The effectiveness of this technique is demonstrated by a large number of computer simulations on the assignment problem and the N-queen problem of different sizes.