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Document Type : Latin Dissertation
Language of Document : English
Record Number : 150625
Doc. No : ET22417
Main Entry : Anil Cheriyadat
Title Proper : LIMITATIONS OF PRINCIPAL COMPONENT ANALYSIS FOR DIMENSIONALITY-REDUCTION FOR CLASSIFICATION OF HYPERPSECTRAL DATA
Note : This document is digital این مدرک بصورت الکترونیکی می باشد
Abstract : It is a popular practice in the remote-sensing community to apply principalcomponent analysis (PCA) on a higher-dimensional feature space to achievedimensionality-reduction. Several factors that have led to the popularity of PCA includeits simplicity, ease of use, availability as part of popular remote-sensing packages, andoptimal nature in terms of mean square error. These advantages have prompted theremote-sensing research community....-...,..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 : TL45633.pdf
Title and statement of responsibility and : LIMITATIONS OF PRINCIPAL COMPONENT ANALYSIS FOR DIMENSIONALITY-REDUCTION FOR CLASSIFICATION OF HYPERPSECTRAL DATA [Thesis]
 
 
 
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