Since process and environmental variations can no longer be ignored in high-performance microprocessor designs, it is necessary to develop techniques for computing the sensitiviti...
Sanjay V. Kumar, Chandramouli V. Kashyap, Sachin S...
With deep-sub-micron (DSM) technology, statistical timing analysis becomes increasingly crucial to characterize signal transmission over global interconnect wires. In this paper, ...
Clustering is one of the most widely used statistical tools for data analysis. Among all existing clustering techniques, k-means is a very popular method because of its ease of pr...
Multivariate analysis methods such as independent component analysis (ICA) have been applied to the analysis of functional magnetic resonance imaging (fMRI) data to study the brai...
Symbolic execution can be problematic when applied to real applications. This paper addresses two of these problems: (1) the constraints generated during symbolic execution may be ...