It was observed that a dimensionless linear predictive model is better than the nonlinear.
Radial growth rate (mm.h−1) was calculated using linear predictive model [38] according to Eq. 2: r = mu (t - {{lambda }}) (2 where, r is the average radius of colony (mm), µ is the radial growth rate (mm/h), t is the time (h) and λ is the duration of the lag phase (h).
We modeled the OO expression levels and correlation coefficients as a function of their WBC counterparts using linear predictive models.
The form of this sequence is appropriate for modeling the overall tendency of the traffic, using linear predictive models.
These functional groups form the basis of three stabilization rendering parameters, representing the cyclization, dehydrogenation and oxidation reactions that occur during PAN stabilization, and are used as the independent variables of the non-linear predictive model.
Using a linear predictive coding (LPC) procedure, the source model (a model of the sound emitted from the vocal folds) was separated from the filter model (a model of the filter characteristics of the vocal tract), using 20 predictors.
Data driven non-linear predictive models such as Gaussian processes [ 12], neural networks [ 13], particle filters [ 14] have been successfully developed for industrial applications, although designing non-linear models in control theory is difficult task [ 15].
Each reduced size class set is used to create a non-linear cumulative rates model which is linearized to design a linear model predictive controller.
The design of the nonlinear model predictive controller consists of two steps: the first step is to design a linear model predictive controller based on the linear part of the system at each sample instant, then an overall convergent nonlinear part is added to the linear model predictive controller to combine a nonlinear controller using error driven.
