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

Author

Ansari, A.Q. ; Gupta, Neeraj Kumar

Author_Institution

Dept. of Electr. Eng., Jamia Millia Islamia, New Delhi, India

fYear

2011

fDate

11-14 Dec. 2011

Firstpage

1374

Lastpage

1378

Abstract

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.

Keywords

VLSI; electronic engineering computing; fuzzy reasoning; integrated circuit design; learning (artificial intelligence); neural nets; operational amplifiers; NFIS; OTA; SPICE simulation; VLSI design; fuzzy inference system; input-output mapping; membership function generation; neural network; neuro-fuzzy chip; neuro-fuzzy integrated system; on-line learning ability; operational transconductance amplifier; power 21.9 mW; power consumption; Adaptive systems; Fuzzy logic; Fuzzy systems; Neural networks; Training; Transconductance; Very large scale integration; Current Mirror OTA; Multiplier Type OTA; Neuro-Fuzzy integrated system; Operational Transconductance Amplifier;

fLanguage

English

Publisher

ieee

Conference_Titel

Information and Communication Technologies (WICT), 2011 World Congress on

Conference_Location

Mumbai

Print_ISBN

978-1-4673-0127-5

Type

conf

DOI

10.1109/WICT.2011.6141449

Filename

6141449