本文给出了利用自适应神经元学习、修改模糊控制规则的新方法。
This paper proposes a new method to learn fuzzy control rules using adaptive neural element.
提出了一类基于神经元状态估计器的自适应广义极点配置控制，研究了该控制系统的网络结构和权值学习方法。
This paper presents a class adaptive pole assignment control of servo systems based on neural state estimation and develops the system structure and the weight learning algorithms.
该文给出了一种自适应神经元的控制方法，设计了神经元网络作为控制器的智能控制系统，给出了学习规则。
An adaptive neuron control method is presented. By use of this kind of controller, an intelligent control system is designed, and its learning rules are also presented.
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