多层感知器处理多分类问题的计算能力

• 作者: 包园 吴微 张超 杨思博 罗金铭
• 来源期刊: 高等学校计算数学学报
• 学科: 数学
• 年，卷（期）: 2020,（3）
• 页码范围: 277-288
• 页数: 12页
• 分类号: O244
• 语种: 中文

摘要

In this paper,we consider the design of output layer nodes of multiple linear perceptron 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 ≤ 2q 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.

作者信息

序号	姓名	单位	发文数	被引次数	H指数	G指数
1	吴微		22	481	8.0	21.0
2	张超		28	72	5.0	6.0
3	杨思博		1	0	0.0	0.0
4	包园		1	0	0.0	0.0
5	罗金铭		1	0	0.0	0.0