학술논문

Adaptive fuzzy filtering for audio applications using a neuro-fuzzy modelization
Document Type
Conference
Source
Proceedings of International Conference on Neural Networks (ICNN'97) Neural networks Neural Networks,1997., International Conference on. 4:2162-2166 vol.4 1997
Subject
Computing and Processing
Components, Circuits, Devices and Systems
Signal Processing and Analysis
Adaptive filters
Filtering
Signal processing
Additive white noise
Signal analysis
Frequency
Fuzzy logic
Fuzzy sets
Shape
Noise shaping
Language
Abstract
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.