48 resultados para Independent Increment


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In this letter, we use a novel 3-D model, earlier calibrated with experimental results on standard gate commutated thyristors (GCTs), with the aim to explain the physics behind the high-power technology (HPT) GCT, to investigate what impact this design would have on 24 mm diameter GCTs, and to clarify the mechanisms that limit safe switching at different dc-link voltages. The 3-D simulation results show that the HPT design can increase the maximum controllable current in 24 mm diameter devices beyond the realm of GCT switching, known as the hard-drive limit. It is proposed that the maximum controllable current becomes independent of the dc-link voltage for the complete range of operating voltage. © 1980-2012 IEEE.

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Humans develop rich mental representations that guide their behavior in a variety of everyday tasks. However, it is unknown whether these representations, often formalized as priors in Bayesian inference, are specific for each task or subserve multiple tasks. Current approaches cannot distinguish between these two possibilities because they cannot extract comparable representations across different tasks [1-10]. Here, we develop a novel method, termed cognitive tomography, that can extract complex, multidimensional priors across tasks. We apply this method to human judgments in two qualitatively different tasks, "familiarity" and "odd one out," involving an ecologically relevant set of stimuli, human faces. We show that priors over faces are structurally complex and vary dramatically across subjects, but are invariant across the tasks within each subject. The priors we extract from each task allow us to predict with high precision the behavior of subjects for novel stimuli both in the same task as well as in the other task. Our results provide the first evidence for a single high-dimensional structured representation of a naturalistic stimulus set that guides behavior in multiple tasks. Moreover, the representations estimated by cognitive tomography can provide independent, behavior-based regressors for elucidating the neural correlates of complex naturalistic priors. © 2013 The Authors.