This paper deals with the computational model for fuzzy reasoning neural network and its function approximation capability.
研究了模糊推理神经网络计算模型及其连续函数逼近能力。
As one of the most important capability of ANN, function approximation ability can be used to design ANN model, which can characterize certain physics object.
函数逼近能力是ANN具有的重要性能之一，依据ANN具有的函数逼近能力，可用ANN模型去替代一个确定的物理对象。
The related continuity, function approximation ability and computational capability theorems are proved…
证明了相应的连续性定理 ，逼近定理 ，计算能力定理等。
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