Based on the single-layer perceptron model, a relation between sample size and error classifying for the design of fault classifier for the AFR engine is given. 摘要針對基於單層感知器模型的發動機故障進行分類器設計，研究了故障信號的學習樣本容量和分類誤判率之間的關係。
It would be interesting to know whether or not different training sequences have the similar effect on the multiple layers perceptron like it is in the single layer perceptron. 另外，由於單層感知機只能處理單純的直線分割問題，不同樣本訓練順序在多層感知機是否會產生如單層感知機類似的效應，更值得我們做更進一步的研究。
