Improving performance in pulse radar detection using Bayesian regularization for neural network training
DSpace at IIT Bombay
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Title |
Improving performance in pulse radar detection using Bayesian regularization for neural network training
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Creator |
KUMAR, P
MERCHANT, SN DESAI, UB |
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Subject |
backpropagation algorithm
bayesian regularization multi-layered feedforward neural network pulse compression |
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Description |
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
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Publisher |
ACADEMIC PRESS INC ELSEVIER SCIENCE
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Date |
2011-07-12T15:27:41Z
2011-12-26T12:48:57Z 2011-12-27T05:34:30Z 2011-07-12T15:27:41Z 2011-12-26T12:48:57Z 2011-12-27T05:34:30Z 2004 |
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Type |
Article
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Identifier |
DIGITAL SIGNAL PROCESSING, 14(5), 438-448
1051-2004 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 |
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Language |
en
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