...
  • 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Signal processing >Pipelined set-membership approach to adaptive Volterra filtering
【24h】

Pipelined set-membership approach to adaptive Volterra filtering

机译：流水线集成员方法用于自适应Volterra滤波

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Due to the high computational complexity required by Volterra filter, some of its practical implementations consider pipelined adaptive Volterra filter architecture with two layers structure. However, its main challenges are the poor robustness against impulsive noise, slow convergence and high computational complexity for long memory high order expansion on each module. In this paper, we firstly extend the pipelined second-order adaptive Volterra filter to its high order version. Then, to reduce the computational complexity and improve the robust performance of pipelined adaptive Volterra filter architecture, the pipelined adaptive Volterra set-membership (PAVF-SM) algorithm and its robust version (PAVF-RSM) are proposed, which are derived from the least-perturbation property and adaptive approximation principle. Due to the inherent variable step size and nonlinear selective update mechanisms, the proposed PAVF-SM and PAVF-RSM algorithms achieve lower complexity and improved convergence performance. Simulations also verify the improved performance of the PAVF-SM and PAVF-RSM algorithms under Gaussian noise and impulsive noise environments.
机译：由于Volterra滤波器需要很高的计算复杂度，因此其一些实际实现考虑了具有两层结构的流水线自适应Volterra滤波器架构。然而，它的主要挑战是针对脉冲噪声的鲁棒性差，收敛速度慢以及对于每个模块上的长存储器高阶扩展都具有很高的计算复杂性。在本文中，我们首先将流水线二阶自适应Volterra滤波器扩展到其高阶版本。然后，为了降低计算复杂度并提高流水线型自适应Volterra滤波器架构的鲁棒性能，提出了流水线型自适应Volterra集成员（PAVF-SM）算法及其鲁棒版本（PAVF-RSM），该算法从最小-摄动性质和自适应近似原理由于固有的可变步长和非线性选择性更新机制，所提出的PAVF-SM和PAVF-RSM算法实现了较低的复杂度并提高了收敛性能。仿真还验证了在高斯噪声和脉冲噪声环境下，PAVF-SM和PAVF-RSM算法的性能提高。

著录项

  • 来源
    《Signal processing》 |2016年第12期|195-203|共9页
  • 作者

    Sheng Zhang; Jiashu Zhang; Yanjie Pang;

  • 作者单位

    Sichuan Province Key Laboratory of Signal and Information Processing, Southwest Jiaotong University, Chengdu 610031, China;

    Sichuan Province Key Laboratory of Signal and Information Processing, Southwest Jiaotong University, Chengdu 610031, China;

    Sichuan Province Key Laboratory of Signal and Information Processing, Southwest Jiaotong University, Chengdu 610031, China;

  • 收录信息
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Nonlinear filter; Pipelined; Adaptive Volterra filter; Set-membership;

    机译：非线性滤波器流水线;自适应Volterra滤波器集合成员;

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号