Multiresolution denoising for arbitrarily spaced data contaminated with arbitrary noise
Denoising is an essential ingredient of any data processing task because real data are usually contaminated by some amount of uncertainty, error or noise. The ultimate objective in this study is to handle the multiresolution denoising of an arbitrarily spaced multidimensional data set contaminated w...
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University of Surrey
2005
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| Online Access: | http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.418284 |