Adaptive fuzzy filtering for audio applications using a neuro-fuzzy modelization

The paper describes a new denoising technique particularly suited for audio signals affected by white noise. The filtering algorithm is based on adaptive fuzzy rules taking into consideration the local temporal signal characteristics in order to estimate the noise components and consequently eliminate them. For a correct initial setting of the membership functions parameters describing the variables involved in the fuzzy processing, a pre-processing phase based on a neuro-fuzzy network has been implemented. The results of this nonlinear approach compared with classical filtering techniques are found to be attractive especially for non-stationary signals