Bayesian approaches have been proposed by several functional magnetic resonance imaging (fMRI) researchers in order to overcome the fundamental limitations of the popular statistical parametric mapping method. However, the difficulties associated with subjective prior elicitation have prevented the widespread adoption of the Bayesian methodology by the neuroimaging community. In this paper, we ...

The mixture Kalman filter is a general sequential Monte Carlo technique for conditional linear dynamic systems. It generates samples of some indicator variables recursively based on sequential importance sampling (SIS) and integrates out the linear and Gaussian state variables conditioned on these indicators. Due to the marginalization process, the complexity of the mixture Kalman filter is qui...

Meta-analysis can be considered a multilevel statistical problem, since information within studies is combined in the presence of potential heterogeneity between studies. Here a general multilevel model framework is developed for meta-analysis to combine either summary data or individual patient outcome data from each study, and to include either study or individual level covariates that might ...

The implementation and analysis strategies plays vital role to minimize THD in Multilevel inverter. The modulation technique regards Selective harmonic Elimination and Space Vector Pulse Width Modulation(SVPWM).Multilevel inverters has tremendous application in the area of high-power and mediumvoltage energy control. In this paper simulation of SVPWM is performed for cascaded H bridge Multileve...

Multilevel representations have been studied extensively by arti cial intelligence researchers. We present a general method that utilizes the multilevel paradigm to attack the problem of performing multidiscipline engineering design optimization in the presence of many local optima. The method uses a multidisciplinary simulator at multiple levels of abstraction, paired with a multilevel search ...