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For 2D affine motion model, the black-border constraints can be exactly modeled by linear inequalities as in (8).
Interestingly, this quantization operation may be exactly modeled by an additive noise channel, i.e., we have (hat {xi }_{t} = xi _{t} + n_{t}), where the noise n t is zero-mean with variance ({sigma _{n}^{2}}) and independent of ξ t, see [31] for details.
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However, earlier works have showed that the coefficients may not exactly be modeled by using a normal PDF.
Indeed, Model Predictive Controllers are widely used in the control of complex systems, which hardly can be exactly represented by a model of known structure.
These processes were affected by a number of parameters and may not be exactly represented by any model.
As the I V curve of a small DSC is obtained, the performances of DSC modules with any geometrical character can be exactly simulated by this model.
Based on the sector nonlinearity concept of Tanaka and Wang (2001) [1], the uncertain nonlinear system can be exactly represented by T S fuzzy models.
Due to the random component added to the synthetic datasets, it can not be expected that the input parameters used for the degradation model will be exactly reproduced by the fitting procedure.
A reduction can only be exact in terms of the input/output behavior of the system which can be exactly preserved by a reduced model.
If the model is correct and the parameters are known, then the population covariance matrix would be exactly reproduced by SEM (except for sampling variation).
Therefore, the impact of risk factors estimated by the logistic models, even without statistical significance, may not be exactly the absence shown by adjusting the primary sampling unit.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com