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A hybrid genetic/BP algorithm and its application for radar target classification

机译:一种混合遗传/ BP算法及其对雷达目标分类的应用

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In this paper, a general purposed real valued genetic algorithm model is presented. For the training of neural networks, the hybrid algorithm integrates the real valued algorithm with the well known BP algorithm. It is used to the training of a feedforward neural networks for radar target classification based on 1-D range profile. 50 range profile samples from the real radar data of each of the three aircrafts are used to train the neural network and another 50 range profile samples are used to test the classification performance. The proposed method can also be used to other optimization problems.
机译:本文介绍了一般的被用途的真正的实值遗传算法模型。 为了训练神经网络,混合算法将真实值算法与众所周知的BP算法集成。 它用于基于1-D范围分布训练用于雷达目标分类的前馈神经网络。 来自三种飞机中的每一个的真实雷达数据的50个范围型材样本用于训练神经网络,另一个50个距离样本用于测试分类性能。 该方法还可用于其他优化问题。

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