Sentence examples for minimum variance approach from inspiring English sources

This paper presents the design of an incremental discrete variable structure controller, based on the minimization of the generalized minimum variance approach, to deal with multivariable plants and to handle different time delay of control loops between the input output pairs.

The most popular of them are the diagonal loading approaches [12] and constrained minimum variance approaches [13 16].

The second problem, the robustness of the tracking, is addressed using a minimum variance control approach.

The advantage of combining EEG and MEG data was also evaluated using other inverse operators, such as sparse source reconstruction (Ding and Yuan 2013) on simulated data, linearly constrained minimum variance beamformer approach on simulated and auditory data (Hong et al. 2013) or Multiple Sparse Prior methods on face evoked responses (Henson et al. 2009).

Indeed, the computational complexity of the proposed method is roughly the same as the classic minimum variance linear prediction analysis approach.

The first group covers self-tuning PID controllers, the second group of described controllers is based on the polynomial approach and the third group contains the controllers derived on the other approaches (minimum variance control etc).

It has been shown in [11] that converges to the solution of the conventional optimum array beamforming based on the linearly constrained minimum variance (LCMV) criterion when approaches infinity.

A new linear filter is designed in the linear minimum variance sense using the innovation analysis approach.

The EKF makes use of a first-order Taylor approximation of the state transition and thus does not approach the true minimum variance estimate when the linearization error is non-negligible.

The first group covers PID adaptive algorithms using traditional Ziegler-Nichols method for the setting of the controller parameters, the second group of described controllers is based on the pole placement design and the third group contains the controllers derived on the other approaches (dead-beat, minimum variance etc).

Typical supervised signal extraction approaches are, e.g., multichannel Wiener filtering (MWF) [8, 9] or beamforming approaches, such as linearly constrained minimum variance (LCMV) beamformer [10].