Fault Categorization of Small Quantities of Real Data using Neural NetworksPOMPES PAR TRANSITIONS MULTIPLES

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" Fault Categorization of Small Quantities of Real Data using Neural NetworksPOMPES PAR TRANSITIONS MULTIPLES "

Document Type	:	Latin Dissertation
Language of Document	:	English
Record Number	:	153361
Doc. No	:	ET25153
Main Entry	:	Erik Murray Laxdal
Title Proper	:	Fault Categorization of Small Quantities of Real Data using Neural NetworksPOMPES PAR TRANSITIONS MULTIPLES
Note	:	This document is digital این مدرک بصورت الکترونیکی می باشد
Abstract	:	In this thesis, an algorithm will be discussed for determining if a pattern classifier/recog-nizer can be developed based upon a sparse set of exemplars. Specifically, it will addressfault classification issues associated with cable television distribution networks and usesignatures of observed faults to train our neural networks. The focus is to derive a training.
Subject	:	Electericl tess
	:	برق
electronic file name	:	TL49383.pdf
Title and statement of responsibility and	:	Fault Categorization of Small Quantities of Real Data using Neural NetworksPOMPES PAR TRANSITIONS MULTIPLES [Thesis]