In this paper,we consider the design of output layer nodes of multiple linear perception network for solving r-class classification problems（r≥ 3）.In general,the output layer is designed in an "one-to-one" approach.Instead,we will adopt a "binary-coding" approach to build the output layer,which contains q nodes such that 2q-1 ＜r ≤2 q with q≥ 2 and outputs a binary code of the number i if an input belongs to the i-th class.In particular,for multiple linear perceptrons with four hidden nodes,we prove the following result:One-to-one approach can solve an r-class classification problem with r≤16 by using r output nodes,while our binary-coding approach can solve the same problem by using q（q≤4） output nodes.
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