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		题名	作者	年代	出处	被引量
	1	A Novel Feature Selection Framework for Automatic Web Page Classification显示文摘The number of Internet users and the number of web pages being added to WWW increase dramatically every day.It is therefore required to automatically and e?ciently classify web pages into web directories.This helps the search engines to provide users with relevant and quick retrieval results.As web pages are represented by thousands of features,feature selection helps the web page classifiers to resolve this large scale dimensionality problem.This paper proposes a new feature selection method using Ward s minimum variance measure.This measure is first used to identify clusters of redundant features in a web page.In each cluster,the best representative features are retained and the others are eliminated.Removing such redundant features helps in minimizing the resource utilization during classification.The proposed method of feature selection is compared with other common feature selection methods.Experiments done on a benchmark data set,namely WebKB show that the proposed method performs better than most of the other feature selection methods in terms of reducing the number of features and the classifier modeling time.	J.Alamelu Mangai V.Santhosh Kumar S.Appavu alias Balamurugan	2012	International Journal of Automation and computing2012，9，4：	3
	2	Understanding the Structure of a Large Heroin Distribution Network: A Quantitative Analysis of Qualitative Data显示文摘	Mangai Natarajan	2006	Journal of Quantitative Criminology2006，，2：	1
	3	Integrating region and edge information for texture segmentation using a modified constraint satisfaction neural network显示文摘	GUPTA L MANGAI U G DAS S	2008	Computer Vision and Image Understanding2008，26，8：	1
	4	A Survey of decision fusion and feature fusion strategies for pattern classification显示文摘	Mangai U Samanta S Das S	2010	Insti- tution of Electronics and Telecommunication Engineers2010，27，12：	1
	5	A survey of decision fusion and feature fusion strategies for pattern classification显示文摘	MANGAI U G SAMANTA S DAS S	2010	IETE Technical review2010，27，4：	1
	6	A survey of decision fusion and feature fusion strategies for pattern classification显示文摘	MANGAI U G SAMANTA S DAS S		0，，12：	1
	7	Subspace-based Clustering and Retrieval of 3-D Objects显示文摘	Mangai MA Gounden N A	2013	Computers&Electrical Engineering2013，39，3：	1
	8	Integrating region and edge infor- mation for texture segmentation using a modified constraint satisfac- tion neural network显示文摘	Gupta L Mangai U G Das S	2008	Image and Vision Computing2008，26，8：	1
	9	A parallel complex divider architecture based on DCD iterations for computing complex division in MVDR beamformer显示文摘This paper presents a hardware architecture using mixed pipeline and parallel processing for complex division based on dichotomous coordinate descent(DCD) iterations. The objective of the proposed work is to achieve low-latency and resource optimized complex divider architecture in adaptive weight computation stage of minimum variance distortionless response(MVDR)algorithm. In this work, computation of complex division is modeled as a 2×2 linear equation solution problem and the DCD algorithm allows linear systems of equations to be solved with high degree of computational efficiency. The operations in the existing DCD algorithm are suitably parallel pipelined and the performance is optimized to 2 clock cycles per iteration. To improve the degree of parallelism, a parallel column vector read architecture is devised.The proposed work is implemented on the field programmable gate array(FPGA) platform and the results are compared with state-of-art literature. It concludes that the proposed architecture is suitable for complex division in adaptive weight computation stage of MVDR beamformer. We demonstrate the performance of the proposed architecture for MVDR beamformer employed in medical ultrasound imaging applications.	KIDAV Jayaraj U SIVA Mangai N M PERUMAL M Pillai	2018	Journal of Systems Engineering and Electronics2018，29，6：	0

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