defuzzifier circuit is one of the most important parts of fuzzy logic controllers that determine the output accuracy. the center of gravity method (cog) is one of the most accurate methods that so far been presented for defuzzification. in this paper, a simple algorithm is presented to generate triangular output membership functions in the mamdani method using the multiplier/divider circuit and...

A novel two-level Boolean minimization method is presented here. In contrast to classical methods the cover of the on-set is computed first, whilst no implicants are known to this phase. The implicants are being derived from the source terms by their expansion directed by the cover. This allows us to generate group implicants directly, avoiding the time-consuming implicant expansions and reduct...

Defuzzifier circuit is one of the most important parts of fuzzy logic controllers that determine the output accuracy. The Center Of Gravity method (COG) is one of the most accurate methods that so far been presented for defuzzification. In this paper, a simple algorithm is presented to generate triangular output membership functions in the Mamdani method using the multiplier/divider circuit and...

unknown noise and artifacts present in medical signals with  non-linear fuzzy filter will be estimate and then removed. an adaptive neuro-fuzzy interference system which has a nonlinear  structure presented  for the noise function prediction by before samples. this paper is about a neuro-fuzzy method to estimate unknown noise of electrocardiogram (ecg) signal. adaptive neural combined with fuzz...