An anomaly detection model using candid covariance-free incremental principal component analysis for wireless sensor networks

An anomaly detection model using candid covariance-free incremental principal component analysis for wireless sensor networks

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Bibliographic Details
Main Author: Qasem, Murad Abdo Rassam
Format: Thesis
Published: 2013
Subjects:
QA75 Electronic computers
Computer science
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id my-utm-ep.36706
record_format uketd_dc
spelling my-utm-ep.367062014-05-05T04:02:06Z An anomaly detection model using candid covariance-free incremental principal component analysis for wireless sensor networks 2013 Qasem, Murad Abdo Rassam QA75 Electronic computers. Computer science 2013 Thesis http://eprints.utm.my/id/eprint/36706/ phd doctoral Universiti Teknologi Malaysia, Faculty of Computing Faculty of Computing
institution Universiti Teknologi Malaysia
collection UTM Institutional Repository
topic QA75 Electronic computers
Computer science
spellingShingle QA75 Electronic computers
Computer science
Qasem, Murad Abdo Rassam
An anomaly detection model using candid covariance-free incremental principal component analysis for wireless sensor networks
description
format Thesis
qualification_name Doctor of Philosophy (PhD.)
qualification_level Doctorate
author Qasem, Murad Abdo Rassam
author_facet Qasem, Murad Abdo Rassam
author_sort Qasem, Murad Abdo Rassam
title An anomaly detection model using candid covariance-free incremental principal component analysis for wireless sensor networks
title_short An anomaly detection model using candid covariance-free incremental principal component analysis for wireless sensor networks
title_full An anomaly detection model using candid covariance-free incremental principal component analysis for wireless sensor networks
title_fullStr An anomaly detection model using candid covariance-free incremental principal component analysis for wireless sensor networks
title_full_unstemmed An anomaly detection model using candid covariance-free incremental principal component analysis for wireless sensor networks
title_sort anomaly detection model using candid covariance-free incremental principal component analysis for wireless sensor networks
granting_institution Universiti Teknologi Malaysia, Faculty of Computing
granting_department Faculty of Computing
publishDate 2013
_version_ 1747816447267045376

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