Abstract
The optimization methodology proposed in this work is inspired to [1] and is named Possibilistic Worst-Case Distance (PWCD). This scheme has been tested on an application related to the MOS device sizing of a two stage Operational Transconductance Amplifier circuit (OTA) [2]. In order to model the uncertainties arising from circuit parameter simulations the fuzzy set theory, introduced by Zadeh [3], has been used. A linearization of the circuit performances as function of circuit parameters has been fitted as suitable approximation in a finite range, this choice was suggested to reduce the computational cost related to simulations of the real design. By means of linearization the circuit performances were fuzzyfied and a possibility measure of performance failure was minimized. The proposed case study will show that the possibilistic approach to the worst case analysis, even though less accurate for indirect yield estimation with respect to the probabilistic one, can identify an optimal design in yield terms. Furthermore the possibilistic methodology allows to develop calculation without any statistical hypothesis or sensitive analysis.
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Sciacca, E., Spinella, S., Anile, A.M. (2007). Possibilistic Worst Case Distance and Applications to Circuit Sizing. In: Castillo, O., Melin, P., Ross, O.M., Sepúlveda Cruz, R., Pedrycz, W., Kacprzyk, J. (eds) Theoretical Advances and Applications of Fuzzy Logic and Soft Computing. Advances in Soft Computing, vol 42. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72434-6_29
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DOI: https://doi.org/10.1007/978-3-540-72434-6_29
Publisher Name: Springer, Berlin, Heidelberg
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