Abstract The aim of the paper is to give a coherent account of the robustness approach based on shrinking neighborhoods in the case of i.i.d. observations, and add some theoretical...
This paper presents an efficient statistical design methodology that allows simultaneous sizing for performance and optimization for yield and robustness of analog circuits. The s...
Robust model fitting is important for computer vision tasks due to the occurrence of multiple model instances, and, unknown nature of noise. The linear errors-in-variables (EIV) m...
In this paper we propose a RObust Analog Design tool (ROAD) for post-tuning analog/RF circuits. Starting from an initial design derived from hand analysis or analog circuit synthe...
Xin Li, Padmini Gopalakrishnan, Yang Xu, Lawrence ...
Abstract. Robust Optimization (RO) is a modeling methodology, combined with computational tools, to process optimization problems in which the data are uncertain and is only known ...