Distributed Polytope ARTMAP: A vigilance-free ART network for distributed supervised learning

摘要：

The Polytope ARTMAP (PTAM) suggests that irregular polytopes are more flexible than the predefined category geometries to approximate the borders a-mong the desired output predictions. However, the categories cannot cover input space efficiently for the limited category expansion. This paper proposes Distributed Polytope ARTMAP (DPTAM), which seeks to combine the advantages of distributed coding and PTAM. DPTAM not only allows different polytopes expanding towards the input pattern simultaneously, but also permits of simplex overlap which is from the same desired prediction. Simulations show that DPTAM retains PTAM accuracy while ameliorating memory compression and region cover efficiency with less sensitivity to the variation of minimum simplex angle.

作者: Leonardo Liao Yongqiang Wu

作者单位: Southwest Electronics and Telecommunication Technology Research Institute Chengdu, 610041 P.R China

会议类型: 国际会议

会议名称: The Second International Joint Conference on Computational Science and Optimization(CSO 2009)(2009 国际计算科学与优化会议)

会议地点: 三亚

会议语种:英文

页码: 501-504

在线出版日期: 2009-04-24（万方平台首次上网日期，不代表论文的发表时间）