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Title: Simulation of Non-Gaussian Non-translation Stochastic processes using Karhunen-Loeve Expansion
Keywords: translation process, non-translation process, Karhunen-Loeve expansion, spectral representation, Compatibility
Issue Date: 17-May-2006
Citation: LI LIANGBO (2006-05-17). Simulation of Non-Gaussian Non-translation Stochastic processes using Karhunen-Loeve Expansion. ScholarBank@NUS Repository.
Abstract: This thesis presents a study on the use of Karhunen-Loeve (K-L) expansion to simulate non-Gaussian, non-translation stochastic processes. The K-L expansion has been successfully applied to the simulation of highly skewed non-Gaussian processes based on the prescribed covariance and marginal distribution functions. In this thesis, the non-Gaussian K-L expansion is first applied to the spectral representation as a special case when the random process is indexed over a domain that is much larger than the correlation distance. Subsequently, the difference in simulating the spectral representation using the non-Gaussian K-L approach and the standard translation approach is investigated. It is demonstrated that different processes can be generated satisfying the same target spectral density function and the same target marginal distribution function regardless of their compatibility. Finally, the non-Gaussian K-L expansion technique is further extended to simulate multi-dimensional non-Gaussian stochastic fields.
Appears in Collections:Master's Theses (Open)

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