Name
Abstract | ||
|---|---|---|
In this paper the application of neural networks to Automatic Target Recognition (ATR) using a High Range Resolution radar is studied. Both Multi-layer Perceptrons (MLP) and Radial Basis Function Networks (RBFN) have been used. RBFNs can achieve very good results with a considerably small size of the training set, but they require a high number of radial basis functions to implement the classifier rule. MLPs need a high number of training patterns to achieve good results but when the training set size is higher enough, the performance of the MLP-based classifier approaches the results obtained with RBFNs, but with lower computational complexity. Taking into consideration the complexity of the HRR radar data, the choice between these two kind of neural networks is not easy. The computational capability and the available data set size should be considered in order to choose the best architecture. MLPs must be considered when a low computational complexity is required, and when a large training set is available; RBFNs must be used when the computational complexity is not constrained, or when only few data patterns are available. |
Year | DOI | Venue |
|---|---|---|
2003 | 10.1007/3-540-44869-1_71 | IWANN '03 Proceedings of the 7th International Work-Conference on Artificial and Natural Neural Networks: Part II: Artificial Neural Nets Problem Solving Methods |
Keywords | Field | DocType |
training set,high number,neural network,training pattern,lower computational complexity,low computational complexity,high range resolution radar,computational capability,neural solutions,computational complexity,large training set,good result,multi layer perceptron,radial basis function,radial basis function network,automatic target recognition | Radar,Radial basis function,High range resolution,Pattern recognition,Automatic target recognition,Computer science,Artificial intelligence,Classifier (linguistics),Artificial neural network,Perceptron,Machine learning,Computational complexity theory | Conference |
Volume | ISSN | Citations |
2687 | 0302-9743 | 1 |
PageRank | References | Authors |
0.35 | 9 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| roberto gilpita | 1 | 57 | 7.79 |
| P. Jarabo-Amores | 2 | 29 | 4.10 |
| raul vicenbueno | 3 | 55 | 7.55 |
| Manuel Rosa-Zurera | 4 | 192 | 36.27 |