Recurrent online kernel recursive least square algorithm for nonlinear modeling

• المؤلفون الرئيسيون: Fan, Haijin, Song, Qing, Xu, Zhao
• مؤلفون آخرون: School of Electrical and Electronic Engineering
• التنسيق: Conference or Workshop Item
• اللغة: English
• منشور في: 2013
• الموضوعات: DRNTU::Engineering::Electrical and electronic engineering
• الوصول للمادة أونلاين: https://hdl.handle.net/10356/101013; http://hdl.handle.net/10220/16315
• المؤسسة: Nanyang Technological University

In this paper, we proposed a recurrent kernel recursive least square (RLS) algorithm for online learning. In classical kernel methods, the kernel function number grows as the number of training sample increases, which makes the computational cost of the algorithm very high and only applicable for of...