Name
Title | ||
|---|---|---|
A Parallel Implementation Of A Growing Som Promoting Independent Neural Networks Over Distributed Input Space |
Abstract | ||
|---|---|---|
Self-Organizing maps can discover topological and multidimensional patterns using a variety of methods. We apply a parallel algorithm proposed by the authors (ParaSOM), which yields closer and denser approximations than other methods in a fraction of iterations, to a two-dimensional pattern in a parallel environment to demonstrate a high degree of neuron independence. In a second implementation, pieces of a two-dimensional input space are distributed over a network and processed by independent ParaSOM algorithms. |
Year | DOI | Venue |
|---|---|---|
2006 | 10.1109/IJCNN.2006.246789 | 2006 IEEE INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORK PROCEEDINGS, VOLS 1-10 |
Keywords | Field | DocType |
iterative methods,parallel algorithm,parallel algorithms,neural network | Iterative method,Parallel algorithm,Computer science,Theoretical computer science,Artificial intelligence,Artificial neural network,Machine learning | Conference |
ISSN | Citations | PageRank |
2161-4393 | 2 | 0.38 |
References | Authors | |
6 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| John Hammond | 1 | 2 | 0.38 |
| Daniel Macclean | 2 | 2 | 0.38 |
| Iren Valova | 3 | 136 | 25.44 |