Fast Adaptive Algorithm to Extract Multiple Principal Generalized Eigenvectors

摘要：

We consider adaptively extracting multiple principal generalized eigenvectors, which can be widely applied in modern signal processing. By using deflation technique, the problem is reformulated into an unconstrained minimization problem. An adaptive sequential algorithm based on Newton method is proposed to solve this problem. In order to improve its real-time performance, a parallel version of this algorithm is provided on the basis of certain approximation. Furthermore, a two-layer neural network is constructed to execute the adaptive algorithm. The simulation results demonstrate the effectiveness of the proposed algorithms.

作者: Jian Yang Xi Chen

作者单位: Department of Automation University of Science and Technology of China Hefei, Anhui , China 230027

会议类型: 国际会议

会议名称: 2011 Seventh International Conference on Natural Computation(第七届自然计算国际会议 ICNC 2011)

会议地点: 上海

会议语种:英文

页码: 417-421

在线出版日期: 2011-07-26（万方平台首次上网日期，不代表论文的发表时间）