Particle filters (PFs) are powerful samplingbased inference/learning algorithms for dynamic Bayesian networks (DBNs). They allow us to treat, in a principled way, any type of prob...
Arnaud Doucet, Nando de Freitas, Kevin P. Murphy, ...
Consideration of pairs of transition in probabilistic simulation allows power estimation for digital circuits in which inertial delays can filter glitches [5]. However, the merit ...
With reference to digital input power amplifier for automotive audio applications, the paper presents an exhaustive exploration of the huge mixed-signal space to find optimal trad...
The placement of passive components significantly influences the EMI behavior of power electronic systems. Particularly filter components are affected by magnetic field coupling r...
Power consumption in data centres is a growing issue as the cost of the power for computation and cooling has become dominant. An emerging challenge is the development of “envir...