Sentence examples for minimizing the quadratic from inspiring English sources

Minimizing the quadratic from the x-step is equivalent to solving a system of linear equations composed of structured matrices, all of which represent convolutions.

The proposed loop shaping method is based on the shaping of the open-loop transfer function in the Nyquist diagram through minimizing the quadratic error between the actual and the desired open loop transfer functions in the frequency domain.

For the most recent, a fitting method of L-moments is described in detail for the estimation of its three parameters, also a fitting by minimizing the quadratic mean error through numerical optimization is proposed.

The optimal control for the active suspension is determined by minimizing the quadratic performance index composed of the state variables and control efforts, and then the active suspension structure has a cascade feedback loop composed of the Kalman filter and the optimal controller.

The computation of loading matrices is performed by minimizing the quadratic cost function (10).

For simple linear regression the parameters w and b are determined by minimizing the quadratic loss l2(f(x i ) − y i ) = (f(x i ) − y i )2 (Figure 1A), across all of the data points.

The goal is to design a dynamic Markov jump controller such that the closed loop system minimizes the quadratic functional cost of the system over a finite horizon period of time.

The controllers not only guarantee that all poles of the closed-loop system remain inside the specified disk D α,r), but also minimize the quadratic performance index (for the case of guaranteed cost D-stabilization) or the exogenous disturbance attenuation level (for the case of H∞ D-stabilization).

In Section 3, we show the existence of an optimal control u ∈ U which minimizes the quadratic cost function.

We need to show the existence of (u^ in {mathcal {U}}_{mathrm{ad}} ) that minimizes the quadratic cost functional J.

We try to minimize the quadratic norm of the differences between data (g o ) and model response (g r ) plus a term of smoothing (Eq. (1)).