Adaptive beamforming with small data set
62 p.
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2011
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sg-ntu-dr.10356-468002023-07-04T15:51:33Z Adaptive beamforming with small data set Sohaib Sajid. Ser Wee School of Electrical and Electronic Engineering DRNTU::Engineering::Electrical and electronic engineering 62 p. This dissertation presents a performance analysis of narrowband beamformers under the low sample support constraint. Finite sampling involved due to limited data snapshots in the construction of Co-variance matrix by traditional Minimum Variance Distortionless Response (MVDR) beamformer results in the appearance of residual correlations in signal to source Co-variance matrix even tough the sources are not correlated in actual. Presence of these residual correlations significantly degrades the performance of MVDR beamformer. Under conditions of low sample support, a low-rank solution of the Minimum Variance Distortionless Response (MVDR) beamformer yields a higher output Signal-to-Interference-plus-Noise Ratio (SINR) than die full-rank MVDR beamformer. Master of Science (Communications Engineering) 2011-12-23T09:56:34Z 2011-12-23T09:56:34Z 2010 2010 Thesis http://hdl.handle.net/10356/46800 Nanyang Technological University application/pdf |
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DRNTU::Engineering::Electrical and electronic engineering Sohaib Sajid. Adaptive beamforming with small data set |
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62 p. |
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Ser Wee |
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Ser Wee Sohaib Sajid. |
format |
Theses and Dissertations |
author |
Sohaib Sajid. |
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Sohaib Sajid. |
title |
Adaptive beamforming with small data set |
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Adaptive beamforming with small data set |
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Adaptive beamforming with small data set |
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Adaptive beamforming with small data set |
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Adaptive beamforming with small data set |
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adaptive beamforming with small data set |
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2011 |
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http://hdl.handle.net/10356/46800 |
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1772828654278017024 |