Sea clutter Target Recognition Based on Modular Neural Network

DOI

10.2991/emim-16.2016.252How to use a DOI?

Keywords

BP neural network; Sea clutter; Modular network; Prediction model

Abstract

Sea clutter is a highly nonlinear signal; it has a non-stationary nature both in time and space. Many scholars found that sea clutter data are chaotic. This indicates that the system has some internal rules, but it is difficult to make an analytic formula. The BP neural network with self-organizing fuzzy spatial mapping ability of artificial happens to be a powerful tool for such kind of problem. But it is not enough to get a better result for sea clutter target recognition use an only predict method. So we use modular integrated neural network method in this experiment. The results show that the modular integrated neural network can improve the recognition performance.

Copyright

© 2016, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Hongjie Yi
AU  - Guangrong Ji
AU  - Jinghua Liu
AU  - Lin Jia
PY  - 2016/04
DA  - 2016/04
TI  - Sea clutter Target Recognition Based on Modular Neural Network
BT  - Proceedings of the 6th International Conference on Electronic, Mechanical, Information and Management Society
PB  - Atlantis Press
SP  - 1230
EP  - 1235
SN  - 2352-538X
UR  - https://doi.org/10.2991/emim-16.2016.252
DO  - 10.2991/emim-16.2016.252
ID  - Yi2016/04
ER  -