Name
Abstract | ||
|---|---|---|
In this paper, by adding a nonlinear self-feedback to the maximum neural network (MNN), we propose a new algorithm for the clique vertex-partition problem that introduces richer and more flexible dynamics and can prevent the network from getting stuck at local minima. A large number of instances have been simulated to verify the proposed algorithm. |
Year | DOI | Venue |
|---|---|---|
2004 | 10.1007/978-3-540-28647-9_71 | ADVANCES IN NEURAL NETWORKS - ISNN 2004, PT 1 |
Keywords | Field | DocType |
neural network,local minima | Partition problem,Nonlinear system,Clique,Computer science,Stochastic neural network,Recurrent neural network,Probabilistic neural network,Maxima and minima,Artificial intelligence,Artificial neural network,Machine learning | Conference |
Volume | ISSN | Citations |
3173 | 0302-9743 | 0 |
PageRank | References | Authors |
0.34 | 5 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jiahai Wang | 1 | 604 | 49.01 |
| Xinshun Xu | 2 | 390 | 32.51 |
| Zheng Tang | 3 | 2 | 1.25 |
| Weixing Bi | 4 | 8 | 1.68 |
| Xiaoming Chen | 5 | 6 | 1.83 |
| Yong Li | 6 | 12 | 2.53 |