An overview on optimized NLMS algorithms for acoustic echo cancellation
نویسندگان
چکیده
منابع مشابه
An overview on optimized NLMS algorithms for acoustic echo cancellation
Acoustic echo cancellation represents one of the most challenging system identification problems. The most used adaptive filter in this application is the popular normalized least mean square (NLMS) algorithm, which has to address the classical compromise between fast convergence/tracking and low misadjustment. In order to meet these conflicting requirements, the step-size of this algorithm nee...
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An acoustic echo cancellation structure with a single loudspeaker and multiple microphones is, from a system identification perspective, generally modelled as a single-input multiple-output system. Such a system thus implies specific echo-pathmodels (adaptive filter) for every loudspeaker tomicrophone path. Due to the often large dimensionality of the filters, which is required tomodel rooms wi...
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In this paper, starting from a robust statistics (RS) adaptive approach presented in a previous work entitled the combined NLMS-Sign (CNLMS-S) adaptive filter, an automatic combination technique with similar performances is proposed. Thus, in order to obtain better performances in acoustic echo cancellation (AEC) setups than with the normalized least-mean square (NLMS) algorithm, in the CNLMS-S...
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A stereophonic echo canceler is proposed based on the Normalized LMS algorithm with orthogonal correction factors (NLMS-OCF). The echo canceler is modeled using a two-input single-output finite-impulse-response (FIR) structure. NLMSOCF updates the echo canceler coefficients based on multiple input vectors, while NLMS adapts the coefficients based on a single input vector. The proposed algorithm...
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One of the limitations of linear adaptive echo cancellers is nonlinearities which are generated mainly in the loudspeaker. The complete acoustic channel can be modelled as a nonlinear system convolved with a linear dispersive echo channel. Two new acoustic echo canceller models are developed to improve nonlinear performance. The first model consists of a time-delay feedforward neural network (T...
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ژورنال
عنوان ژورنال: EURASIP Journal on Advances in Signal Processing
سال: 2015
ISSN: 1687-6180
DOI: 10.1186/s13634-015-0283-1