提出了一种具有自适应类警戒参数的模糊ARTMAP神经网络，为不同的模糊ART的类族设置了不同的警戒测试参数，并在学习过程中进行适应调整。还提出了新的非交叠超方形以及非交叠的Nested超主形的建立与扩展学习规则。

A new fuzzy ARTMAP neural network with adaptive cluster vigilance parameter is proposed. Each cluster (hyper rectangle) has its own vigilance parameter which is adaptively adjusted during the training procedure. And a new learning law that defines the establishments and expansions for either non overlapped hyper rectangles or non overlapped nested hyper rectangles is proposed. The proposed neural network can obtain high prediction rate, which has resolved not only the problem of memory stability and plasticity but also the problem of non convex input patterns, both of which exist in traditional fuzzy ARTMAP neural networks. The simulations of applying the new net to palm prints recognition demonstrate its good performance.