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dc.creatorTodorovic, Milosen_US
dc.descriptionDue to the character of the original source materials and the nature of batch digitization, quality control issues may be present in this document. Please report any quality issues you encounter to, referencing the URI of the item.en_US
dc.descriptionIncludes bibliographical references (leaves 129-132).en_US
dc.descriptionIssued also on microfiche from Lange Micrographics.en_US
dc.description.abstractThe wavelet transform represents a powerful signal processing tool with a variety of applications. The main reason for the growing interest in this field of signal processing is its ability not only to decompose a signal into its frequency components, but also, as opposed to the Fourier transform, to provide a non-uniform division of the frequency domain. The decomposed signals possess a powerful time-frequency localization property, which is one of the major benefits provided by the use of the wavelet transform. This property is extremely important for the analysis of power system disturbances. Large numbers of disturbances occur in a very short time period within the analyzed signal while having the broad frequency spectrum (temporal localization). Some disturbances spread over the entire signal duration while having their significant frequency content very close in frequency to the "normal" signal components (frequency localization). In spite of the great attention given to the application of wavelets in power system analysis, only a small number of papers deal with the details of selecting the right wavelet suitable for a given application. The need for defining a systematic approach for choosing the best wavelet for an application at hand still exists. This thesis focuses on finding the best approach to the wavelet selection for the analysis of typical power system disturbances. The research topics addressed in this document include: o initial theoretical selection of wavelets based on the typical wavelets characteristics such as compact support, orthogonality, symmetry, number of vanishing moments, and regularity. o definition of a criterion for wavelet performance assessment. o implementation of wavelet performance assessment approaches in MATLAB and Simulink. o conclusions regarding the suitability of the specific wavelet for the given application.en_US
dc.publisherTexas A&M Universityen_US
dc.rightsThis thesis was part of a retrospective digitization project authorized by the Texas A&M University Libraries in 2008. Copyright remains vested with the author(s). It is the user's responsibility to secure permission from the copyright holder(s) for re-use of the work beyond the provision of Fair Use.en_US
dc.subjectelectrical engineering.en_US
dc.subjectMajor electrical engineering.en_US
dc.titleSelection of wavelets for analysis of power system disturbancesen_US
dc.typeThesisen_US engineeringen_US
dc.format.digitalOriginreformatted digitalen_US

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