Artificial neural network approaches and compressive sensing techniques for stochastic process estimation and simulation subject to incomplete data
This research is themed around development of tools for discrete analysis of stochastic processes subject to limited or missing data; more specifically, estimation of stochastic process power spectra from which new process time-histories may be simulated. In this context, the author proposes three n...
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University of Liverpool
2015
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| Online Access: | http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.706620 |