一种基于模式匹配的模糊模型及其神经网络实现(英)

A pattern-Matching Based Fuzzy Model and Its Identification by Neural Network

通过模糊模式匹配概念，引入了一种新的模糊模型，并用神经网络方法对该模型进行辨识，以获得更高的精度．仿真实验表明，该模糊模型不仅简单易行，而且比通常的模糊模型有更强的辨识能力，另外，本文还讨论了模型的进一步求精，以及模糊神经网络的一般性问题．

This paper proposes a fuzzy model based on pattern-matching. In order to identifythe new fuzzy model,a fuzzy neural network(FNN) is employed to obtain the optimal parameters.With simulation experiment, the performance of FNN modeling is compared with that of otherfuzzy modeling methods.