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Model reduction allows to overcome this limitation, through the generation of simplified system models with outputs acceptably similar to those of the original system or model.
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Consider a DNN acoustic model with outputs corresponding to tied CD states.
The method is applied to a second order model with output perturbations.
For the extended steering model with output equation whose elements can be measured by equipped sensors, the optimal regulator is introduced so that the vehicle can tracks the reference path.
For the extended steering model with output equation whose elements can be measured by equipped sensors, the H∞ optimal controller is introduced so that the vehicle can tracks the reference path.
We used HTK[22], with some changes in order to replace the usual Gaussian mixture models with the outputs of the MLP.
Unfortunately this model showed very poor calibration performance, although this result may be partly due to the limitations of the HL test or the recalibration procedure for score models with discrete outputs.
While for probability models, calibration can be assessed using the Hosmer-Lemeshov test [ 13], this test may not be completely appropriate for models with discrete outputs (such as scoring systems).
However, this method may lead to unreliable results and the Hosmer-Lemeshov test (developed for logistic-regression models) may not be appropriate for models with discrete outputs such as scoring systems [ 13].
Models with multivariate output are often used in practical structural systems.
Linear dynamical models with nonlinear output maps can represent a wide range of industrial processes.
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