Variable step-size NLMS algorithms designed for echo cancellation
ABSTRACT A major issue in echo cancellation is to recover the near-end signal from the error signal of the adaptive filter. In this paper, we use this requirement in order to design a family of variable step-size normalized least-mean-square (VSS-NLMS) algorithms. The main parameter that is needed within these algorithms is the near-end signal power estimate. Several solutions for this problem are presented and evaluated in terms of different practical aspects (i.e., available parameters, complexity). Due to their specific characteristic, these VSS-NLMS algorithms are equipped with good robustness features against near-end signal variations (e.g., double-talk) and can be reliable candidates for real-world echo cancellation scenarios.
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- "Another VSS-NLMS scheme is to include the echo-path change detection statistic (n) proposed in  and  to our algorithm. The resulting variable step size is updated as "
ABSTRACT: Numerous variable step-size normalized least mean-square (VSS-NLMS) algorithms have been derived to solve the dilemma of fast convergence rate or low excess mean-square error in the past two decades. This paper proposes a new, easy to implement, nonparametric VSS-NLMS algorithm that employs the mean-square error and the estimated system noise power to control the step-size update. Theoretical analysis of its steady-state behavior shows that, when the input is zero-mean Gaussian distributed, the misadjustment depends only on a parameter $\beta$ controlling the update of step size. Simulation experiments show that the proposed algorithm performs very well. Furthermore, the theoretical steady-state behavior is in very good agreement with the experimental results.IEEE Transactions on Signal Processing 04/2012; 60(4):2055-2060. DOI:10.1109/TSP.2011.2181505 · 2.79 Impact Factor
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- "Minimizing with respective to µ result in the following       which force to to zero Substitute the value of µ in "
ABSTRACT: Acoustic echo arise in hand free communication environment due to poor voice coupling between Microphone and Loudspeaker. This paper shows the implementation of Acoustic echo cancellation using gradient based LMS algorithm it also focused on NLMS algorithm to remove the unwanted echo and increase the quality of speech in communication applications .The LMS algorithms uses the estimates of the gradient vector from the available data.LMS and NLMS incorporates an iterative procedure that updates weight vector in the direction opposite of the gradient vector which evenly leads to the minimum mean square error.
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ABSTRACT: The paper presents an acoustic echo cancellation application of three variable step-size Normalized Least Mean Square (NLMS) algorithms: the simple VSS-NLMS (SVSS-NLMS), the new non-parametric (NEW-NPVSS-NLMS) and the practical VSS-NLMS (PVSS-NLMS) algorithms. Simulations were performed in two scenarios: single-talk and double-talk. We will prove that the PVSS-NLMS algorithm can be used in a double-talk situation without using a double-talk detector (DTD). The capabilities and performances of the algorithms are analyzed in terms of convergence rate, tracking and robustness, but also from other practical point of view, such as available parameters.