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A high-performance fully programmable membership function generator based on 10 nm gate-all-around CNTFETs
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DOI：10.1016/j.aeue.2020.153293.png)
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Abstract
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This paper presents a novel fully programmable membership function generator (MFG) based on carbon nanotube field effect transistors (CNTFETs). The proposed CNTFET-based MFG has full control over the output characteristics such as height, and position independently. The proposed design can produce four different membership functions only by calibrating the external control bias voltages. Moreover, two peripheral transmission gates are utilized to provide controllability over the slope of the generated membership functions in a wide range. The primary advantage of the proposed MFG compared to its counterparts is the ability to control the slope of the resulted membership functions entirely and separately using only two external bias voltages without the need for changing the device physical dimensions. The simulation results demonstrate that the proposed design improves the power, delay, and layout area, on average by, 72%, 55%, and 33% as compared to the previous designs. Furthermore, the proposed MFG shows only 2.13% RMS error, and 5.65% maximum absolute error for the generated Gaussian trapezoidal membership function as compared to the ideal form. Our results certify that the proposed CNTFET-based MFG has the potential to be used as a promising platform for fuzzy inference systems in deep nanoscale technology nodes. (C) 2020 Elsevier GmbH. All rights reserved.
Keywords:
Fuzzy logic
Gate-All-Around (GAA)
Carbon Nanotube FET (CNTFET)
MFG
Fuzzifier
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