Multi-Objective Genetic Algorithms Based Approach to Optimize the Small Signal Parameters of Gate Stack Double Gate MOSFET


In this paper, the small signal parameters behavior of Gate Stack Double Gate (GSDG) MOSFET are studied and optimized using multi-objective genetic algorithms (MOGAs) for deep submicron CMOS analog circuits' applications. The transconductance and the OFF-current are the small signal parameters which have been determined by the proposed analytical explicit expressions in saturation and subthreshold regions. According to the proposed analytical models, the objectives functions which are the prerequisite of genetic algorithm are formulated to search for optimal small signal parameters to obtain the best electrical performances of the devices for analog applications. Thus, the encouraging obtained results may be of interest to practical applications.


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