In recent years, sparse representation originating from signal compressed sensing theory has attracted increasing interest in computer vision research community. However, to our b...
Power minimization under variability is formulated as a rigorous statistical robust optimization program with a guarantee of power and timing yields. Both power and timing metrics...
— With process variation becoming a growing concern in deep submicron technologies, the ability to efficiently obtain an accurate estimate of failure probability of SRAM compone...
State-equivalence based reduction techniques, e.g. bisimulation minimization, can be used to reduce a state transition system to facilitate subsequent verification tasks. However...
– Many embedded system designs usually impose (hard) read-time constraints on tasks. Thus, computing a tight upper bound of the worst case execution time (WCET) of a software is ...