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.
- SourceAvailable from: Silviu Ciochina[show abstract] [hide abstract]
ABSTRACT: In acoustic echo cancellation (AEC) applications, where the acoustic echo paths are extremely long, the adaptive filter works most likely in an under-modeling situation. Most of the adaptive algorithms for AEC were derived assuming an exact modeling scenario, so that they do not take into account the under-modeling noise. In this letter, a variable step-size normalized least-mean-square (VSS-NLMS) algorithm suitable for the under-modeling case is proposed. This algorithm does not require any a priori information about the acoustic environment; as a result, it is very robust and easy to control in practice. The simulation results indicate the good performance of the proposed algorithm.IEEE Signal Processing Letters 02/2008; · 1.67 Impact Factor
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ABSTRACT: Over the last decade, a certain computationally efficient, rapidly converging adaptive filtering algorithm has been independently discovered many times. The algorithm can be viewed as a generalization of the normalized LMS (NLMS) algorithm that updates on the basis of multiple input signal vectors. This article compares and discusses the different approaches to and embellishments of the basic algorithm, and contrasts the various interpretations from different perspectives.IEEE Signal Processing Letters 09/1996; · 1.67 Impact Factor
Conference Proceeding: Novel variable step size nlms algorithms for echo cancellation.[show abstract] [hide abstract]
ABSTRACT: In this paper we present two new variable step size (VSS) methods for adaptive filters. These VSS methods are so effective, they eliminate the need for a separate double-talk detection algorithm in echo cancellation applications. The key feature of both approaches is the introduction of a new near-end signal energy estimator (NESEE) that provides accurate and computationally efficient estimates even during double-talk and echo path change events. The first VSS algorithm applies the NESEE to the recently proposed Nonparametric VSS NLMS (NPVSS-NLMS) algorithm. The resulting algorithm has excellent convergence characteristics with an intrinsic immunity to double-talk. The second approach is somewhat more ad hoc. It is composed of a combination of an efficient echo path change detector and the NESEE. This VSS method also has excellent convergence, double talk immunity, and computational efficiency. Simulations demonstrate the efficacy of both proposed algorithms.Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2008, March 30 - April 4, 2008, Caesars Palace, Las Vegas, Nevada, USA; 01/2008 · 4.63 Impact Factor