递归复合型模糊神经网络结构研究

针对一类能够有效引入过程先验知识的复合型模糊神经网络，研究了其动态结构． 通过对复合型模糊神经网络的函数网络的第二层引入动态递归环节，使其具有动态映射能力 ，实现了对动态系统的良好响应．本文采用了动态非线性模型对其进行仿真研究，结果 表明，对于处理动态非线性系统，此动态复合模糊神经网络较之静态网络在收敛速度、预测 精度和网络规模等方面都有较大的改善．

STUDY ON THE STRUCTURE OF RECURRENT COMPOUND FUZZY NEURAL NETWORK

This paper studies the dynamic structure of a type of compound fuzzy neural network, which can effectively use the process knowledge. The network has the ability of dynamic mapping by adding recurrent nodes in the second layer of the function network of the compound fuzzy neural network, so it would realize the good response to the dynamic system. Simulation has been made with a dynamic nonlinear model, and the result shows that the compound dynamic fuzzy neural network is better than the static network in convergence rate and prediction precision, and has a smaller network size.