Neuro-Fuzzy integrated system and its VLSI design for generating membership function

In this paper, a Neuro-Fuzzy integrated system, which is based on fuzzy inference system using on-line learning ability of neural network is presented. By using on-line learning procedure, the proposed neuro-fuzzy integrated system (NFIS) can be used to construct an input-output mapping based on fuzzy if-then rules and the tuning of the parameters of membership function. The membership functions for NFIS have been realized using operational transconductance amplifier (OTA). Attention is given to design the circuits with low power consumption 2.91mW and size less than 0.65 mm² within the neuro-fuzzy chip. SPICE simulations showed that they are suitable to real time application.