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Yield estimation for analog integrated circuits remains a time-consuming operation in variation-aware sizing. State-of-the-art statistical methods such as ranking-integrated Quasi-Monte-Carlo (QMC), suffer from performance degradation if the number of effective variables is large (as typically is the case for realistic analog circuits). To address this problem, a new method, called AYLeSS, is proposed...
It is known that the operating-point driven (OPD) analog sizing methods have clear advantages compared with the sizing methods of directly using transistor width and length as the decision variables. However, new analog sizing algorithms using OPD technique in modern technologies have seldom been reported in recent years. One of the main reasons is that with the scaling down of the technologies, the...
Monte-Carlo (MC) simulation is still the most commonly used technique for yield estimation of analog integrated circuits, because of its generality and accuracy. However, although some speed acceleration methods for MC simulation have been proposed, their efficiency is not high enough for MC-based yield optimization (determines optimal device sizes and optimizes yield at the same time), which requires...
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