Title :
Ship´s classification by its magnetic signature
Author :
Do Amaral, J. A A Arantes ; Botelho, P.L. ; Ebecken, N.F.F. ; Caloba, L.P.
Author_Institution :
IPaM, Ilha do Gov., Rio de Janeiro, Brazil
Abstract :
A ship´s classification by its magnetic signatures is of great importance in the development of magnetic mines. This work concerns the use of a neural network classification system combined with the relevant features method to solve this problem
Keywords :
feature extraction; feedforward neural nets; learning (artificial intelligence); multilayer perceptrons; pattern classification; ships; magnetic signature; neural network classification system; relevant features method; ship classification; Acoustic measurements; Classification algorithms; Magnetic field measurement; Magnetic materials; Magnetization; Magnetometers; Marine vehicles; Modems; Neural networks; Neurons;
Conference_Titel :
Neural Networks Proceedings, 1998. IEEE World Congress on Computational Intelligence. The 1998 IEEE International Joint Conference on
Conference_Location :
Anchorage, AK
Print_ISBN :
0-7803-4859-1
DOI :
10.1109/IJCNN.1998.687146
