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While humans have an incredible capacity to acquire new skills and alter their behavior as a result of experience, enhancements in performance are typically narrowly restricted to the parameters of the training environment, with little evidence of generalization to different, even seemingly highly related, tasks.
The block diagram of the optimization strategy to find the parameters of the training model is depicted in Fig. 4.
This is compared against the parameters of the training sequences for the various activities using the modified distance metric of (11). Figure 11 Activity recognition results over a sequence involving a single human performing various activities.
The visual parameters of the training audio-visual data are classified into several visual clusters by k-means method, and for each cluster two individual HMMs are trained independently using the associated audio and visual parameters, and also a Fused HMM is trained.
Figure 1C and Table 3 display the confusion matrix and quality parameters of the training results.
Major arguments in favour of the specificity of training effects come from studies that relate behavioural improvement directly to electrophysiological parameters of the training performance.
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We used CRFsuite (http://www.chokkan.org/software/crfsuite/) as an implementation of CRF and optimized its parameters on the training set of each corpus by 10-fold crossvalidation.
A set of experimental data, covering a large range of parameters, for the training and testing of neural networks is used.
Open image in new window Fig. 2 Influence of the vigilance parameter on the training set clustering.
The web crippling strength is also introduced in closed-form solution based on the parameters of the trained NN.
To deal with the time-varying parameters of the train motion dynamics, the piecewise constant model is introduced to describe the train dynamics with variable parameters.
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