本篇论文提出一个类神经网路分类器来学习多类的分离模糊资讯。
This paper presents a multiclass neural network classifier to learn disjunctive fuzzy information in the feature space.
医学诊断；机器学习；倒传递网路；适应性类神经模糊推论系统。
Medical Diagnosis; Machine Learning; Back-Propagation Neural Network; Adaptive Neural Fuzzy Inference System.
该模型采用基于神经网路理论的模糊模型参数辨识方法，很适合于复杂系统的模糊预测和控制。
The model is suitable for fuzzy prediction and control of complex system because the recognition method of fuzzy module parameters based on the theory of neural network is adopted.
文中探讨了一种用于提取模糊规则的RBF神经网络结构，提出了基于此网路结构的模糊隶属度函数学习算法，最后给出了用于验证该算法有效性的仿真实例。
The learning algorithm of membership function based on the RBF Neural Network is discussed and an example is given to demonstrate the validity of this algorithm.
文中探讨了一种用于提取模糊规则的RBF神经网络结构，提出了基于此网路结构的模糊隶属度函数学习算法，最后给出了用于验证该算法有效性的仿真实例。
The learning algorithm of membership function based on the RBF Neural Network is discussed and an example is given to demonstrate the validity of this algorithm.
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