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Design of a Low Power Analog and Multi-shaped Fully Programmable Twin-Cell Membership Function Generator Circuit in 65 nm CMOS Technology

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This paper presents a new approach for implementing an analog fully programmable membership function generator (MFG) with twin-cell topology which can operate in Transconductance-mode. The proposed multi-shaped MFG circuit is… Click to show full abstract

This paper presents a new approach for implementing an analog fully programmable membership function generator (MFG) with twin-cell topology which can operate in Transconductance-mode. The proposed multi-shaped MFG circuit is capable of generating the trapezoidal, triangular, S- and Z-shaped membership functions. Also, a full programmability disposition in all parameters of height, position and width is achievable. To make this purpose, a simple structure of complementary differential pairs is utilized which changing of their applied input constant voltages and bias current led into programming, independently. Moreover, the proposed MFG architecture has a stellar functionality which makes it suitable for implementing as a general-purpose fuzzy logic controller. Since in this proposed MFG approach, only 26 transistors are used, the chip area and total power dissipation can be decreased to 552 µm 2 and 83.8 µW, respectively, which is reduced in comparison with the other works. The proposed MFG circuit is simulated in 65 nm standard CMOS technology with a single supply voltage of 1.2 V. The post-layout simulation results show that the proposed twin-cell MFG circuit is in great collusion which indicates a high delicacy of the proposed design, and the circuit presents the profit of negligible linearity error less than 5.2%. Furthermore, this proposed circuit is compared with a simulated MFG circuit named the comparative MFG, and the exported results show the improved functionality of the proposed twin-cell MFG, specifically.

Keywords: mfg; circuit; membership; twin cell

Journal Title: Circuits, Systems, and Signal Processing
Year Published: 2021

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