...
  • 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Signal processing >An efficient Kalman filter for the identification of low-rank systems
【24h】

An efficient Kalman filter for the identification of low-rank systems

机译：用于识别低秩系统的有效卡尔曼滤波器

获取原文
获取原文并翻译 | 示例
   

获取外文期刊封面封底 >>

       
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

System identification problems are very difficult in the scenario of long length impulse responses, raising challenges in terms of convergence, complexity, and accuracy of the solution. However, we can take advantage of the characteristics of the impulse response, in order to improve the overall performance. In this context, a recently introduced approach exploits a Kronecker product decomposition of the impulse response in tandem with low-rank approximations. Also, a recursive least-squares (RLS) algorithm was developed based on this idea, showing appealing results for the identification of low-rank systems, like typical echo paths. In this short communication, we propose a Kalman filter tailored for the identification of such low-rank systems. Simulations performed in the context of echo cancellation indicate that the proposed algorithm outperforms the regular Kalman filter, but also its RLS-based counterpart. (C) 2019 Elsevier B.V. All rights reserved.
机译：在长脉冲响应的情况下，系统识别问题非常困难，这在解决方案的收敛性，复杂性和准确性方面提出了挑战。但是，我们可以利用脉冲响应的特性，以提高整体性能。在这种情况下，最近引入的方法利用低秩近似与脉冲响应的Kronecker乘积分解。同样，基于此思想开发了一种递归最小二乘（RLS）算法，该算法显示出用于识别低秩系统（如典型回波路径）的诱人结果。在简短的交流中，我们提出了一种为识别此类低秩系统而量身定制的卡尔曼滤波器。在回声消除的上下文中执行的仿真表明，所提出的算法优于常规的卡尔曼滤波器，但也优于基于RLS的算法。 （C）2019 Elsevier B.V.保留所有权利。

著录项

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