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The hard target-trained networks were trained with 110-h transcribed data.
The soft target-trained networks were trained with 300-h untranscribed data using outputs from the fMLLR teacher DNN.
Rats were trained with cocaine (0.1 10 mg/kg, i.p).
The control group subjects were trained with traditional method.
The IC networks were trained with Matlab's Bayesian regularization module.
Both algorithms were trained with 70% of the historical database.
The intervention significantly increased participants' business activity, but only if they were trained with a friend.
"You had officers who were trained with great skill to ride and play polo".
On a different day, the same patients were trained with a random decoder.
Monkeys were trained with a baseline of either nicotine or THC self-administration (as described above).
FNN and RBF network were trained with particle swarm optimization (PSO) for higher forecast accuracy.
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