This paper proposes several improved CMOS analog circuits for neuro-fuzzy network

including Gaussian-like membership function circuit

minimization circuit

and a centroid algorithm defuzzier circuit without using division.A two-input/one-output neuro-fuzzy network composed of these circuits is implemented and testified for non-linear function approximating.All the circuits have been fabricated in SMIC 0.18- μ m CMOS technology.Experiment results show that all the proposed circuits provide characteristics of high operation capacity

high speed

and simple structures.They are very suitable for rapid implementation of high-speed complex neuro-fuzzy networks.