Sea clutter Target Recognition Based on Modular Neural Network
Hongjie Yi, Guangrong Ji, Jinghua Liu, Lin Jia
Available Online April 2016.
- https://doi.org/10.2991/emim-16.2016.252How to use a DOI?
- BP neural network; Sea clutter; Modular network; Prediction model
- 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.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
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 - 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 - https://doi.org/10.2991/emim-16.2016.252 ID - Yi2016/04 ER -