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dc.creatorSarimveis, Haralambos
dc.date.accessioned2012-06-07T22:29:20Z
dc.date.available2012-06-07T22:29:20Z
dc.date.created1992
dc.date.issued1992
dc.identifier.urihttp://hdl.handle.net/1969.1/ETD-TAMU-1992-THESIS-S245
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 digital@library.tamu.edu, referencing the URI of the item.en
dc.descriptionIncludes bibliographical references.en
dc.description.abstractNot availableen
dc.format.mediumelectronicen
dc.format.mimetypeapplication/pdf
dc.language.isoen_US
dc.publisherTexas A&M University
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
dc.subjectchemical engineering.en
dc.subjectMajor chemical engineering.en
dc.subject.lcshNeural networks (Computer science)en
dc.subject.lcshNonlinear control theory.en
dc.subject.lcshAdaptive control systems - Mathematical models.en
dc.subject.lcshProcess control - Mathematical models.en
dc.titleArtificial neural networks for input-output dynamic modeling of nonlinear processesen
dc.typeThesisen
thesis.degree.disciplinechemical engineeringen
thesis.degree.nameM. S.en
thesis.degree.levelMastersen
dc.type.genrethesisen
dc.type.materialtexten
dc.format.digitalOriginreformatted digitalen


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