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The phenomena of generalization and transfer are seen in the tendency of laboratory subjects conditioned to respond to a particular stimulus to respond as well to similar stimuli beyond the original conditions of training.
We directly tackle a multi-carrier system model and solve the optimality conditions of training signals for LMMSE estimator in MIMO-OFDM systems.
This work is important because the optimality conditions of training signals for LMMSE estimation in MIMO-OFDM systems have been mathematically proved.
This is a clear advantage over GMMs, for which a significant performance reduction is often observed when the noise conditions of training and test data are unmatched.
From this perspective, the DNN and GMM are of no difference, since both can benefit from matched acoustic conditions of training and testing, by either re-training or adaptation.
Interestingly, the optimality conditions of training signals for LMMSE estimator in MIMO-OFDM systems are basically in line with design principles known from single-carrier MIMO systems; training signals across transmit antennas should be orthogonal and training signals should be equi-powered.
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Dynamometer records were made next to the locomotive of a freight train for different conditions of train handling.
Moreover, operation conditions of trains under the local information are analyzed in detail, and the improved method can describe the behaviors of acceleration and deceleration of trains.
In addition, these instruments measure the irregularities under load and, therefore, in the same operating conditions of trains; however, they should solve the problem of inertial reference frame being vehicle-integrated measuring systems.
However, a condition of training with speech sounds that would allow testing this hypothesis was not included in that study.
According to the report the workers living arrangements were 'subhuman... an overcrowded wooden shelter, with no beds, no adequate electricity or sanitary facilities.' In 2010 the construction site for the San Antonio Dam was closed down for two months due to abusive labour conditions, lack of training, and poor living conditions which caused a high accident rate.
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