A Fast Convergence and Robust Algorithm for Adaptive ⅡR Notch Filter

摘要：

This paper aims to improved the convergence rate, noise robustness and less computational complexity. The proposed algorithm is for a second order adaptive IIR notch filter. It is established based on a new memory less nonlinear gradient algorithm and a least mean ρ-power error criterion with a value of ρ equal to unity. The proposed algorithm is very attractive due to their computational efficiencies and improved convergence properties. It is revealed by extensive simulations that it can produce significantly improved frequency estimates in both Gaussian and impulsive noise scenarios compared with the new memoryless nonlinear gradient algorithm and the other existing gradient-type algorithms. Several simulated results are provided to show the superiority of the proposed algorithm.

作者: Chawalit Benjangkaprasert Pornpimon Tupchai Rachu Punchalard Orlarp Sangaroon Kanok Janchitrapongyej

作者单位: Research Center for Communications and Information Technology (ReCCIT), and Department of Industrial Department of Telecommunication Engineering Mahanakorn University of Technology Nong-Chok, Bangkok,

会议类型: 国际会议

会议名称: 8th International Conference on Neural Information Processing(ICONIP 2001)(第八届国际神经信息处理大会)

会议地点: 上海

会议语种:英文

页码: 487-490

在线出版日期: 2001-11-14（万方平台首次上网日期，不代表论文的发表时间）