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In this contribution, we present some recent advances in the modeling of unknown nonlinearities by adaptive Volterra filters. In particular, a system identification scenario in the form of the nonlinear acoustic echo cancelation problem is considered, which is most challenging due to large kernel sizes and excitation by colored (noise) and/or nonstationary signals (speech). After reviewing the general...
Nonlinear acoustic echo cancellers (NLAEC) are becoming increasingly important in hands-free applications. However, in some situations, an NLAEC is inferior to a linear AEC, especially when the channel generates a negligible (or no) nonlinear echo. In general, the ratio of the linear to nonlinear echo signal power is unknown a priori, and will vary over time, thus making it difficult to know if an...
This paper presents a method for estimating the optimum memory size for identification of an unknown second-order Volterra kernel. As these structures may imply considerable computational demands, it is highly desirable to design adaptive realizations with a minimum number of coefficients. Therefore, we propose a combination scheme comprising two Volterra filters with time-variant sizes of the actually...
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