基于遗传BP算法的神经网络目标分类器的研究

Research on Neural Network Classifier of Target Based on Genetic-backpropagation Algorithm

首先阐述了水下目标识别的研究发展和系统组成 ,然后提出了一种基于遗传BP算法训练神经网络目标分类器的新方法。实验结果表明采用新方法的神经网络分类器比采用改进BP算法的神经网络分类器具有更优的分类效果。

The development and system composition of underwater target recognition system is expounded at first, and then a novel method for training neural network target classifier by using genetic-backpropagation algorithm is proposed. The result of experiment shows that the performance of neural network target classifier based on genetic-backpropagation algorithm is better than that of neural network target classifier based on the improved backpropagation algorithm.