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Document Type : Latin Dissertation
Language of Document : English
Record Number : 149851
Doc. No : ET21643
Main Entry : Xuejun Zhu
Title Proper : ANOMALY DETECTION THROUGH STATISTICS-BASED MACHINE LEARNING FOR COMPUTER NETWORKS
Note : This document is digital این مدرک بصورت الکترونیکی می باشد
Abstract : I would like to thank my advisor, Dr. Jionghua Jin. Without her guidance andkindly support, I might not have the opportunity to explore the field of reliability andquality engineering. Also thank Dr. Zhisheng Zhang to discuss many issues together. Iwould like to thank members of my committee, Dr. Askin, Dr. Szidarovszky, Dr. Zeng,and Dr. Hariri. I appreciate their help in both my course work and research projects.I would like to thank my friends, former and current graduate students in theDepartment of Systems..tested for theQ1 PC1 bus cardBoth these projects mere sofixare des elopment efforts tonards contributing to dlfferentaspects of Roboucs and lZ1echatronics projects m the Controls and Roboucs Group..
Subject : Electericl tess
: برق
electronic file name : TL44820.pdf
Title and statement of responsibility and : ANOMALY DETECTION THROUGH STATISTICS-BASED MACHINE LEARNING FOR COMPUTER NETWORKS [Thesis]
 
 
 
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