Patent ID: 6332136
Filing Date: 2001-12-18
Classification: H03H

Abstract:
A method of fuzzy filtering of a noise signal comprising a plurality of signal samples, the method comprising the steps of:a) defining a current signal sample from among said plurality of signal samples;b) calculating a plurality of difference samples as the difference in absolute value between said current signal sample and each sample of said plurality of signal samples;c) defining distance values between said current signal sample and each sample of said plurality of signal samples;d) determining weight parameters on the basis of said difference samples and said distance values by means of fuzzy logic; ande) weighing said signal samples with said weight parameters so as to obtain a reconstructed current signal sample;f) calculating a noise sample as the difference between said reconstructed current signal sample and said current signal sample;repeating steps (a)-(f) to obtain a plurality of reconstructed current signal samples and a plurality of noise samples;determining a noise maximum variation value on the basis of a maximum value and a minimum value of said noise samples;determining a signal maximum variation value on the basis of a maximum value and a minimum value of said signal samples;determining at least two first classes of membership for said plurality of difference samples, said first classes of membership being defined by functions with sections having as limits said noise and signal maximum variation values;associating with each difference sample a respective difference level of truth in each of said first classes of membership;determining at least two second classes of membership for said distance values;associating with each distance value a respective distance level of truth in each of said second classes of membership;applying fuzzy rules to associate said difference and distance levels of truth with weight values and with respective third classes of membership; anddetermining said weight parameters as a function of said weight values and with pre-determined parameters of said third classes of membership.