Realization of Block Robust Adaptive Filters using Generalized Sliding Fermat Number Transform

International audienceThis paper is about an efficient implementation of adaptive filtering for echo cancelers. First, a realization of an improved Block Proportionate Normalized Least Mean Squares (BPNLMS++) using Generalized Sliding Fermat Number Transform (GSFNT) is presented. Unfortunately, during the double-talk mode, the echo cancelers often diverge. We can cope with this problem by employing a double-talk detector formed by two Voice Activity Detectors (VAD's) . We propose a general system based on the Robust-Block-PNLMS ++ (RBPNLMS++) adaptive filter combined with a post-filter. The general system was implemented with GSFNT which can significantly reduce the computation complexity of the filter implantation on Digital Signal Processing (DSP)

Realization of Block Robust Adaptive Filters using Generalized Sliding Fermat Number Transform

Abstract — This paper is about an efficient implementation of adaptive filtering for echo cancelers. First, a realization of an improved Block Proportionate Normalized Least Mean Squares (BPNLMS ++) using Generalized Sliding Fermat Number Transform (GSFNT) is presented. Unfortunately, during the double-talk mode, the echo cancelers often diverge. We can cope with this problem by employing a double-talk detector formed by two Voice Activity Detectors (VAD ′ s). We propose a general system based on the Robust-Block-PNLMS ++ (RBPNLMS ++) adaptive filter combined with a post-filter. The general system was implemented with GSFNT which can significantly reduce the computation complexity of the filter implantation on Digital Signal Processing (DSP). I