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Thus, the model can be trained by using the prepared training set.
Normal rule class, a set of false alert classification rules, can be trained by using sequential pattern mining approach in an attack-free environment.
We designed our learning control in such a way that it can be trained by using the hearing aid in the same way as a conventional hearing aid with control wheel.
The softmax classifier can be trained by using the L-BFGS algorithm based on a dataset, in order to find an optimal parameter set W (3) for minimizing the cost function ({J_{{text {softmax}}}}left ({mathbf {W}^{(3)}}right)).
In addition, the parameters of HMMs can be trained by using experimentally verified data.
Most tools can be trained by using the desired training sets.
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Neural network controllers are trained by using dynamic backpropagation algorithm.
The ANN model has been trained by using a multi-scale numerical model.
The multilayer perceptron network with a 9-5-1 trainedy was trained by using the back propagation algorithm.
Recurrent and back propagation neural networks are trained by using data generated from best response model.
Second ANN was trained by using these switching angles to generate PWM signals.
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