The phrase "adaptive beamformer" is correct and usable in written English.
It can be used in contexts related to signal processing, telecommunications, or audio engineering, where it refers to a technology that adjusts the characteristics of a beamformer based on the incoming signals.
Example: "The adaptive beamformer significantly improved the clarity of the audio during the conference call by filtering out background noise."
Alternatives: "dynamic beamformer" or "self-adjusting beamformer".
(2) An adaptive beamformer generally adapts its weights during breaks in the target signal [1].
In the MSNWF-DOA system, the optimal estimation of the phase-shifted reference signal ( {e}^{j{phi}_k}{mathbf{r}}_k ) in the minimum mean square error sense can be obtained at the output of the adaptive beamformer B, where the adaptive beamforming weights obtained from the adaptive beamformer A with the MSNWF structure were used.
The RV-LMS adaptive beamformer is shown to have a similar computational complexity as the adaptive MBER beamforming implementation known as the least bit error rate (LBER), imposing only half of the computational requirements of the CV-LMS algorithm.
The performance of an adaptive beamformer is significantly influenced by its array configuration.
Adaptive beamformer analyses of magnetoencephalograms (MEG) have shown promise as a method for functional imaging of cortical processes.
In this paper, we consider robust adaptive beamformer design for multiple-input multiple-output (MIMO) radar systems.
In order to address this problem, robust adaptive beamformers (RABs) have been designed.
We conclude that amygdala activity can be resolved from MEGs with adaptive beamformers with temporal resolution superior to other neuroimaging modalities.
The novelty of such combined adaptive beamformers relies on the use of different adaptive sidelobe cancelling structures which allow the system to achieve robustness in nonstationary noisy environments.
Conventionally, adaptive beamformers are applied to suppress interferences that exist in sidelobe area [1, 2].
Generally, adaptive beamformers have been found to be efficient in applications to suppress localized additive noise sources.
