Nonlinear processing of non-Gaussian stochastic and chaotic deterministic time series
It is often assumed that interference or noise signals are Gaussian stochastic processes. Gaussian noise models are appealing as they usually result in noise suppression algorithms that are simple: i.e. linear and closed form. However, such linear techniques may be sub-optimal when the noise process...
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University of Edinburgh
2000
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| Online Access: | http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.561749 |