New Improved Recursive Least-Squares Adaptive-Filtering Algorithms

作者：Bhotto Md Zulfiquar Ali^*; Antoniou Andreas

来源：IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I-REGULAR PAPERS, 2013, 60(6): 1548-1558.

DOI：10.1109/TCSI.2012.2220452

• Adaptive filters
• adaptive-filtering algorithms
• recursive least-squares algorithms
• forgetting factor
• convergence factor

Two new improved recursive least-squares adaptive- filtering algorithms, one with a variable forgetting factor and the other with a variable convergence factor are proposed. Optimal forgetting and convergence factors are obtained by minimizing the mean square of the noise-free a posteriori error signal. The determination of the optimal forgetting and convergence factors requires information about the noise-free a priori error which is obtained by solving a known L-1 - L-2 minimization problem. Simulation results in system-identification and channel-equalization applications are presented which demonstrate that improved steady-state misalignment, tracking capability, and readaptation can be achieved relative to those in some state-of-the-art competing algorithms.

• 出版日期2013-6