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The stationary solution of these equations is similar to results previously obtained by using statistical linearization.
In section 4.1, the value of ( VARleft[{SINR_{lb}}_d^kright] ) is approximated by using statistical linearization argument.
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The simulation of a non-linear mechanical system is carried out by using statistical, harmonic, and DH linearization techniques.
The experimentally observed heteroscedasticity and perturbations after linearization were taken into account by using statistical weights obtained on the basis of errors propagation law and the modeling of retention by non-weighted and weighted least squares method was performed.
Again, by using the statistical linearization argument, first order Taylor series expansion of ( {SINR_{lb}}_d^k ) around the mean value.
Eventually, the response statistics of the semi-actively controlled structure under random wind excitation are evaluated by using the statistical linearization method, and are compared with those of the passively controlled structure to determine the control efficacy.
The non-linear quantized observation system is linearized statistically by using the generalized statistical linearization technique, with the introduction of a new type of error criterion.
We now study this problem by using the linearization system (2.14) and Theorem 4.5.
And a controller is then designed by using feedback linearization based on the approximated slip ratio.
We then investigate the local stability of the three types of equilibrium points by using the linearization method.
We firstly discuss the existence of the equilibria of model (2) by using a linearization method and the Jacobian matrix.
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