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Least squares support vector machines for direction of arrival estimation with error control and validation

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Please use this identifier to cite or link to this item: http://hdl.handle.net/1928/20277

Least squares support vector machines for direction of arrival estimation with error control and validation

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Title: Least squares support vector machines for direction of arrival estimation with error control and validation
Author: Abdallah, Chaouki T.; Rohwer, Judd A.; Christodoulou, Christos G.
Subject(s): Chaotic communication
Classification algorithms
Direction of arrival estimation
Abstract: The paper presents a multiclass, multilabel implementation of least squares support vector machines (LS-SVM) for direction of arrival (DOA) estimation in a CDMA system. For any estimation or classification system, the algorithm's capabilities and performance must be evaluated. Specifically, for classification algorithms, a high confidence level must exist along with a technique to tag misclassifications automatically. The presented learning algorithm includes error control and validation steps for generating statistics on the multiclass evaluation path and the signal subspace dimension. The error statistics provide a confidence level for the classification accuracy.
Date: 2003-12-01
Publisher: IEEE
Citation: IEEE Global Telecommunications Conference, 2003, 4: 2172-2176
Description: Digital Object Identifier: 10.1109/GLOCOM.2003.1258620
URI: http://hdl.handle.net/1928/20277
ISBN: 0-7803-7974-8

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