Takamitsu Araki

Learn More
Auxiliary variable methods such as the Parallel Tempering and the cluster Monte Carlo methods generate samples that follow a target distribution by using proposal and auxiliary distributions. In sampling from complex distributions, these algorithms are highly more efficient than the standard Markov chain Monte Carlo methods. However, their performance(More)
In Bayesian variable selection, indicator model selection (IMS) is a class of well-known sampling algorithms, which has been used in various models. The IMS is a class of methods that uses pseudo-priors and it contains specific methods such as Gibbs variable selection (GVS) and Kuo and Mallick's (KM) method. However, the efficiency of the IMS strongly(More)
  • T. Araki
  • 2005
This paper presents new power chip concepts such as reverse conducting IGBT (RC-IGBT), which are integrated IGBT with diode and reverse blocking IGBT (RB-IGBT). The RC-IGBT have a big impact for conventional power modules. Because, by using RC-IGBT, we can save resources such as silicon chip (including material itself and production energy) and also save(More)
  • 1