Multivariate Input Vector Space Reconstruction and its Application

摘要：

This paper was concentrated on the reconstruction of multivariate input vector space. Based on evaluating the nonlinear correlation degree between observed variables and output variables, the input variables were selected if the evaluation was strong. Then, C-C method was used to reconstruct an initial input vector space. Finally, FastICA method was expanded to extract the effective independent information and reduce the dimension of initial input vector. Simulation results showed the effectiveness of the reconstructed input vector.

关键词： Nonlinear correlation degree Input vector space reconstruction FastICA

作者: Xi Jianhui Zhang Lei Niu Yanfang Su Ronghui Jiang Liying

作者单位: School of Automation, Shenyang Aerospace University, Shenyang 110136, China AVIC Shenyang Aircraft Corporation, Shenyang 100850, China

会议类型: 国际会议

会议名称: The 24th Chinese Control and Decision Conference (第24届中国控制与决策学术年会 2012 CCDC)

会议地点: 太原

会议语种:英文

页码: 4011-4014

在线出版日期: 2012-05-23（万方平台首次上网日期，不代表论文的发表时间）