THE HOTELLING S TWO-SAMPLE T2 ALGORITHM

Name: THE HOTELLING S TWO-SAMPLE T2 ALGORITHM
Brand: LAP Lambert Academic Publishing
SKU: 9783838326542
Price: 236.02 RON
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STATISTICAL CLASSIFIER: CASE STUDY OF THE HOTELLING S TWO-SAMPLE T2 ALGORITHM IN THE PRESENCE OF NOISE

Autor: Nurbek Saparkhojayev

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Editura: LAP Lambert Academic Publishing

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Matching algorithms or classifiers determine if a previously enrolled instance matches an observed i...

Informații despre carte

Autor

Nurbek Saparkhojayev

Limbă

engleză

Legare

Carte - Carte broșată

Publicat

2010

Pagini

EAN

9783838326542

Enbook ID

07085023

Editura

LAP Lambert Academic Publishing

Greutate

136

Dimensiuni

150 x 220 x 5

Descriere completă

Matching algorithms or classifiers determine if a previously enrolled instance matches an observed instance based on some rules. They return a decision, which consists of three possible answers: match, non-match, and unclassified. A classifier assigns a class label to a sample and then checks the new instance with a sample one. Or, the classifier is trained with example instances so that it learns what class label should be applied to future unknown instances. Classifiers are based on statistical, probabilistic, and decision rules. In applying classifiers, the most important issue is finding the matching rates. Two important rates are the false acceptance rate (FAR) and the false rejection rate (FRR). In this work, we determine the FAR and FRR for the Hotelling s two-sample T2 algorithm applied to the application of matching electronic fingerprints of radio frequency identification (RFID) tags in the presence of simulated noise. The algorithm is found to be a robust classifier for this application.

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THE HOTELLING S TWO-SAMPLE T2 ALGORITHM

STATISTICAL CLASSIFIER: CASE STUDY OF THE HOTELLING S TWO-SAMPLE T2 ALGORITHM IN THE PRESENCE OF NOISE

Informații despre carte

Descriere completă

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