A generalized data windowing scheme for adaptive conjugate gradient algorithms

作者：Zhao Shengkui^*; Man Zhihong; Khoo Suiyang

来源：Signal Processing, 2009, 89(5): 894-900.

DOI：10.1016/j.sigpro.2008.11.007

• Conjugate gradient method
• Adaptive filtering
• LMS algorithm
• Recursive least squares

The performance of the modified adaptive conjugate gradient (CG) algorithms based on the iterative CG method for adaptive filtering is highly related to the ways of estimating the correlation matrix and the cross-correlation vector. The existing approaches of implementing the CC algorithms using the data windows of exponential form or sliding form result in either loss of convergence or increase in misadjustment. This paper presents and analyzes a new approach to the implementation of the CG algorithms for adaptive filtering by using a generalized data windowing scheme. For the new modified CC algorithms, we show that the convergence speed is accelerated, the misadjustment and tracking capability comparable to those of the recursive least squares (RLS) algorithm are achieved. Computer simulations demonstrated in the framework of linear system modeling problem show the improvements of the new modifications.

• 出版日期2009-5
• 单位南阳理工学院