Adaptive beamforming using affine projection algorithms
2000
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Metrics Details
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Conference Paper Description
The dynamic adaptive linear constrained minimum variance (LCMV) beamformer generally uses the normalized LMS (NLMS) algorithm for its robustness and simplicity, but it suffers from a low convergence rate. This paper proposes an alternative beamformer incorporating a simplified fast affine projection (FAP) algorithm, which provides fast convergence speed and low computational complexity. The family of affine projection (AP) algorithms improves its convergence speed significantly due to its decorrelation property. We compare the decorrelation properly of the AP algorithms to that of the spatial smoothing algorithm. The fundamental difference between the two decorrelation properties is clarified
Bibliographic Details
Institute of Electrical and Electronics Engineers (IEEE)
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