An optimized NLMS algorithm for system identification
An optimized normalized least-mean-square (NLMS) algorithm is developed for system identification, in the context of a state variable model. The proposed algorithm is based on a joint-optimization on both the normalized step-size and regularization parameters, in order to minimize the system misalignment. The performance of the proposed joint-optimized NLMS (JO-NLMS) algorithm is evaluated in the framework of acoustic echo cancellation. The JO-NLMS algorithm achieves both fast convergence and tracking, but also low misadjustment.
normalized least-mean-square (nlms) algorithm echo cancellation variable step-size nlms variable regularized nlms adaptive filters