Linearity of the proposed method was assessed by estimating the linear dependence of the obtained peak area ratios on the concentration of EBS.
The DA-optimal design for estimating the linear model parameters is derived analytically.
Orthogonal polynomials were used to estimate the linear and quadratic effects of Cr concentrations.
A statistical technique is developed to estimate the linear and nonlinear parameters of the aeroelastic oscillator.
In the implementation proposed, a nonlinear observer is used to estimate the linear velocities used by the controller.
The new designs can also estimate the linear effects without being correlated with the second-order effects.
A semi-parametric identification approach is developed to estimate the linear subsystem parameters and m points on both nonlinearity borders.
Using historical data, we estimate the linear stochastic plateau production function that explicitly incorporates production risks related to weather.
A method is presented which can estimate the linear and nonlinear damping parameters in a lightly damped system.
We develop and apply our framework to estimate the linear filters of an entire population of retinal ganglion cells while taking into account the effects of common-noise the cells might share.
