一种快速近似RLS算法

Proceedings of TENCON '93. IEEE Region 10 International Conference on Computers, Communications and Automation Pub Date : 1993-10-19 DOI:10.1109/TENCON.1993.328038

M. Chansarkar, U. Desai

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引用次数: 5

摘要

针对自适应信号处理算法的实时应用，提出了一种新的近似RLS算法。结果表明，该算法的计算复杂度与LMS算法相当。给出了算法的收敛性分析，证明了算法在平稳数据的均值和均方意义上是无条件收敛的。结果表明，该算法的收敛速度为n/sup -1/。该算法的收敛特性表明，该算法比LMS算法快得多，但比RLS算法略慢。针对非平稳数据环境，对该算法进行了改进。仿真结果与LMS和RLS算法进行了比较。

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A fast approximate RLS algorithm

Motivated by the real time applications of adaptive signal processing algorithms a new Approximate RLS algorithm is developed. It is shown that the computational complexity of this algorithm is comparable to that of the LMS algorithm. Convergence analysis for this algorithm is presented showing the unconditional convergence of the algorithm in the mean and the mean square sense for stationary data. It is shown that the rate of convergence of this algorithm is n/sup -1/. The convergence characteristics of this algorithm shows that the algorithm is much faster than the LMS algorithm but somewhat slower than the RLS algorithm. Modifications to this algorithm are suggested for use in nonstationary data environment. Simulation results for this algorithm are compared with those for the LMS and the RLS algorithms.<>

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Proceedings of TENCON '93. IEEE Region 10 International Conference on Computers, Communications and Automation

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