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Please use this identifier to cite or link to this item: http://dspace.library.iitb.ac.in/jspui/handle/10054/3366

Title: Improving performance in pulse radar detection using Bayesian regularization for neural network training
Authors: KUMAR, P
MERCHANT, SN
DESAI, UB
Issue Date: 2004
Publisher: ACADEMIC PRESS INC ELSEVIER SCIENCE
Citation: DIGITAL SIGNAL PROCESSING, 14(5), 438-448
Abstract: A better approach for training a multi-layered feedforward network for pulse compression is presented. The Bayesian regularization technique used for training the network for pulse radar detection results in superior performance in terms of signal-to-sidelobe ratio compared to the Backpropagation algorithm. The presented method also has better range resolution performance in terms of resistance to lower input code magnitude ratios. 13-bit Barker code, 31-bit m-sequence and 63-bit m-sequence are used as the signal codes. (C) 2004
URI: http://dx.doi.org/10.1016/j.dsp.2004.06.002
http://dspace.library.iitb.ac.in/xmlui/handle/10054/3366
http://hdl.handle.net/10054/3366
ISSN: 1051-2004
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