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Please use this identifier to cite or link to this item: http://hdl.handle.net/11375/6876
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dc.contributor.advisorWong, K.M.en_US
dc.contributor.authorDahanayake, Wickramaratna Bandulaen_US
dc.date.accessioned2014-06-18T16:37:14Z-
dc.date.available2014-06-18T16:37:14Z-
dc.date.created2010-05-21en_US
dc.date.issued1987en_US
dc.identifier.otheropendissertations/2180en_US
dc.identifier.other2719en_US
dc.identifier.other1323495en_US
dc.identifier.urihttp://hdl.handle.net/11375/6876-
dc.description.abstract<p>Adaptive array processing is considered as a task of bearing estimation and beamforming.</p> <p>The use of the subspace decomposition in bearing estimation is studied. Operator decomposition approach is used to provide a more basic and unified framework to the spectrum representation. This unified approach is then utilized to study the geometric relationships between the conventional, high resolution, and super resolution spectrum estimation techniques.</p> <p>Bearing estimation under coherent signal environment is considered. A methodology is developed to estimate the number of incoming signals and the optimum number of subarrays concurrently.</p> <p>Beamforming is presented in a more general framework. The concept of beamforming as a process of joint bearing estimation and interference cancellation is proposed.</p> <p>Finally, a restart to the array processing and digital signal processing problems in general, is initiated.</p>en_US
dc.subjectElectrical and Computer Engineeringen_US
dc.titleSuper Precision Adaptive Array Processing and Systolic Array Structuresen_US
dc.typethesisen_US
dc.contributor.departmentElectrical and Computer Engineeringen_US
dc.description.degreeDoctor of Philosophy (PhD)en_US
Appears in Collections:Open Access Dissertations and Theses

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