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For controlling these two variables, a multiloop control strategy was designed by using two generalized minimum variance adaptive controllers.
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However, minimum-variance adaptive beamforming algorithm is a complicated algorithm with O(n 3) computational complexity.
The first one is that this technique yields a solution compatible with the integration of the computed multiple-period repetitive controller into a minimum-variance adaptive control scheme.
As a result, minimum-variance adaptive beamforming algorithm for medical ultrasonic imaging is considered in this paper, which shows much higher image quality than that of delay-and-sum beamforming algorithm.
One prominent example of robust beamforming techniques is minimum variance robust adaptive beamforming [34], which accounts for imperfections in the estimation of signal covariance matrices.
A non-linear, adaptive generalized minimum variance (GMV) controller is straightforwardly designed to provide automatic voltage regulator (AVR) and power system stabilizer (PSS) roles.
In the last decade, several fruitful principles to minimum variance distortionless response (MVDR) robust adaptive beamforming (RAB) design have been developed and successfully applied to solve a number of problems in a wide range of applications.
On the other hand, high-quality medical ultrasonic imaging algorithms (e.g., minimum-variance (MV) adaptive beamforming algorithm [11], synthetic aperture imaging algorithm [12]) provide much better image quality, as compared to DAS beamforming algorithm, which can present more anatomical details for complicated diagnostic cases.
Pursuing such an approach, we establish a family of the SDR-related SSP estimators, that encompass a manifold of existing beamforming techniques ranging from traditional matched filter to robust and adaptive spatial filtering, and minimum variance methods.
Adaptive beamforming methods, such as minimum variance distortionless response (MDVR), can effectively extract the desired speech signal from interference and noise.
To perform directional and spatial characterization of recorded sounds, a plane wave decomposition with an adaptive beamforming technique, such as minimum variance distortionless response (MVDR) spatial spectrum estimation, was employed.
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