Adaptive L-filters based on fuzzy rules
Akira Taguchi, Misaki Meguro · 2002
An adaptive smoothing filter is proposed for reducing non-stationary or mixed noises, efficiently. The output of the adaptive filter is the weighted sum of typical five L-filters' outputs. The weights are estimated by using fuzzy rules. Since the antecedents of the fuzzy rules can be composed of several local measurements, it is possible for the proposed filter to adjust its weights to adapt to local data. The performance of the proposed filter is compared to several reported filters.