Data-dependent filtering using the fuzzy inference
Akira Taguchi, Hironori Takashima, F. Russo · 2002
This paper presents a design method of data-dependent filters by using fuzzy inference. Since the antecedents of fuzzy inference can be composed of many local characteristics, it is possible for the proposed filter to adjust its weights to adapt to local data in input signal. The tuning of membership functions of the proposed filter results in LMS like algorithm