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It is shown that by restricting the number of active neurons in a layer of a Boltzmann machine, a sparse distributed coding of the input data can be learned. Unlike Winner-Take-All, this coding reveals the distance structure in the training data and thus introduces proximity in the learned code. Analogous to the normal Radial Basis Boltzmann Machine, the network uses an annealing schedule to avoid...
The transmission lines (TLs) for ITER electron cyclotron heating require extremely low losses, since the 24 MW of power generated by the 170 GHz gyrotrons should be delivered to the plasma with an efficiency of 83% or more. We are developing cold-test techniques to precisely measure the losses in the TL components for ITER, before installation. Experimental results on the measurement of the loss in...
One of the most important tasks in medical image analysis is to detect the absence or presence of disease in an image, without having precise delineations of pathology available for training. A novel method is proposed to solve such a classification task, based on a generalized representation of an image derived from local per-pixel features. From this representation, differences between images can...
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