| Paper: | SPTM-P12.8 | ||
| Session: | Adaptive Systems and Filtering I | ||
| Time: | Friday, May 19, 14:00 - 16:00 | ||
| Presentation: | Poster | ||
| Topic: | Signal Processing Theory and Methods: Adaptive Systems and Filtering | ||
| Title: | STOCHASTIC MODEL FOR THE NLMS ALGORITHM WITH CORRELATED GAUSSIAN DATA | ||
| Authors: | Elen Lobato, Orlando Tobias, Rui Seara, Federal University of Santa Catarina, Brazil | ||
| Abstract: | This paper proposes a new stochastic model for the normalized LMS (NLMS) algorithm under correlated input data. The proposed model is derived without invoking the simplifying assumption that xT(n)x(n) has a chi-square distribution to determine E{1/[xT(n)x(n)/N]}. Under correlated input data that assumption is not correct and thus the resulting model becomes inaccurate. Without considering such simplifying assumption, a high-order hyperelliptic integral has to be computed. The proposed model is based on tackling the solution of that integral. Numerical simulations verify the quality of the proposed model. | ||
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