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本系列文章的工作是在舰船噪声谱图的基础上，利用模糊神经网络对舰船进行分类识别。本文是系列文章的第四篇，研究模糊神经网络用于识别分类．选用了多层前馈神经网络和BP学习算法，推导了学习过程中模糊器参数的调整公式，最后给出1049个样本（41条舰船，63种工况，原始记录长约3．5小时）的识别分类结果，识别正确率大于92％。
The work of this series of articles is based on the ship noise spectrum, the use of fuzzy neural network classification of the ship classification. This article is the fourth in a series of articles to study fuzzy neural networks for identifying categories. The multi-layer feedforward neural network and BP learning algorithm are used to derive the adjustment formula of the fuzzer parameters in the learning process. Finally, 1049 samples (41 ships, 63 operating conditions, original record length of 3.5 hours ) Recognition classification results, the recognition accuracy is greater than 92%.