Superior step-size theorem and its application
With independence assumption, this paper proposes and proves the superior step-size theorem on least mean square (LMS) algorithm, from the view of minimizing mean squared error (MSE). Following the theorem we construct a parallel variable step-size LMS filters algorithm. The theoretical model of the proposed algorithm is analyzed in detail. Simulations show the proposed theoretical model is quite close to the optimal variable step-size LMS (OVS-LMS) model. The experimental learning curves of the proposed algorithm also show the fastest convergence and fine tracking performance. The proposed algorithm is therefore a good realization of the OVS-LMS model.
Keywordsadaptive filtering LMS superior step-size theorem parallel variable step-size LMS filters algorithm
Unable to display preview. Download preview PDF.
- 1.Haykin, S., Adaptive Filter Theory (3rd ed.), Beijing: Publishing House of Electronics Industry, 1998.Google Scholar
- 2.Gu, Y. T., Tang, K., Cui, H. J. et al., Novel variable step-size NLMS algorithm, Journal of Tsinghua Univ. (in Chinese), 2002, 42(1): 15–18.Google Scholar
- 3.Park, M. S., Song, W., Jin, A., Complementary pair LMS algorithm for adaptive filtering, IEICE Trans. Fundamentals, 1998, E81-A(7): 1493–1497.Google Scholar