| 引用本文: | 胡卫东,郁文贤,郭桂蓉.一种有效的神经网络检测器.[J].国防科技大学学报,1997,19(3):16-20.[点击复制] |
| Hu Weidong,Yu Wenxian,Guo Guirong.An Effective Neural Network Detector[J].Journal of National University of Defense Technology,1997,19(3):16-20[点击复制] |
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| 一种有效的神经网络检测器 |
| 胡卫东, 郁文贤, 郭桂蓉 |
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(国防科技大学 ATR 重点实验室 湖南 长沙 410073)
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| 摘要: |
| 本文提出了一种有效的神经网络检测方法。该方法通过高效的自组织学习过程, 使该神经网络对各种噪声或杂波分布能够快速准确地建模, 最终能使在各种噪声分布条件下检测效果均逼近最佳检测器的性能。实验结果验明了该方法的有效性。 |
| 关键词: 检测器, 神经网络, 自组织, 快速建模 |
| DOI： |
| 投稿日期：1996-10-16 |
| 基金项目:国防预研基金资助项目 |
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| An Effective Neural Network Detector |
| Hu Weidong, Yu Wenxian, Guo Guirong |
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(ATR Lab. NUDT, Changsha, 410073)
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| Abstract: |
| An effective detection method based on the neural network is proposed in this paper. By the self-organizing learning in high efficiency, it can model different kinds of noise or clutter rapidly and accurately. This results in a good detection performance, and this detector can approximate the optimal ones on the condition of different statistical distributions. Finally the experiments have proved the effectiveness of this approach. |
| Keywords: detector, neural network, self-organizing, fast modeling |
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