CIVILICA We Respect the Science
(ناشر تخصصی کنفرانسهای کشور / شماره مجوز انتشارات از وزارت فرهنگ و ارشاد اسلامی: ۸۹۷۱)

Programmable Fuzzifier Circuits with High Precision for Analog Neuro-Fuzzy System

عنوان مقاله: Programmable Fuzzifier Circuits with High Precision for Analog Neuro-Fuzzy System
شناسه ملی مقاله: ICEE20_028
منتشر شده در بیستمین کنفرانس مهندسی برق ایران در سال 1391
مشخصات نویسندگان مقاله:

Habib Ghasemizadeh - Urmia Microelectronic Research Laboratory, Urmia, Iran
Amir Fathi
Aghil Ahmadi

خلاصه مقاله:
In this paper, we propose a Membership function Generator (MFG) circuit in the form of Gaussian and trapezoidal for Neuro-fuzzy applications which is programmedby four voltage signals. Two signals define the knees where output signals begin falling or rising, while other ones change the rising or falling slopes of Gaussian and trapezoidalfunctions, independently. So there is no need to change the sizes of transistors or to switch parallel transistors. This is alsocaused the circuit flexibility increases and the chip area decreases. Using two stages, the accuracy of the circuit togenerate Gaussian function is improved. Since three generated functions (small, medium, and large) are produced by a circuit simultaneously, low power consumption with small occupiedarea is obtained. Finally, simulation results which were done by HSPICE (level49) in 0.35μm CMOS process are presented.The Layout of the circuit realized less than 1300μm

کلمات کلیدی:
Fuzzifier, Fuzzy controller, Gaussian function, MFG, Mixed signal

صفحه اختصاصی مقاله و دریافت فایل کامل: https://civilica.com/doc/154241/