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