引用本文: | 罗永光,梁甸农.用于超角分辨的 Hopfield 神经网络方法[J].国防科技大学学报,1992,14(3):64-69.[点击复制] |
Luo Yongguang,Liang Diannong.The Hopfield's Neural Network Method for Superresolution Estimation of the Direction of Arrival[J].Journal of National University of Defense Technology,1992,14(3):64-69[点击复制] |
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用于超角分辨的 Hopfield 神经网络方法 |
罗永光, 梁甸农 |
(电子技术系)
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摘要: |
Hopfield 神经网络用于方位估计可获得高的精度和超分辨力。本文综述有关研究,描述该网络模型及用其于信号处理的一般步骤,用于方位估计的具体形式,讨论提高精度及分辨力的一些措施,指出进一步研究的方向。 |
关键词: 雷达测角精度,信号处理,神经网络 |
DOI: |
投稿日期:1991-02-28 |
基金项目: |
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The Hopfield's Neural Network Method for Superresolution Estimation of the Direction of Arrival |
Luo Yongguang, Liang Diannong |
(Department of Electronic Technology)
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Abstract: |
High accuracy and superresolution of direction of arrival (DOA) can be achieved by means of the Hopfield's neural network (HNN). In this paper a survey for related studies of this field is presented. The HNN's model,the common steps of signal processing with the HNN and the concrete form of estimation of DOA with the HNN are described. Some methods of raising accuracy and improving resolution for it are discussed. The topics for further study are pointed out. |
Keywords: rader angle measurement accuracy,signal processing,neural networks |
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