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Document Type : Latin Dissertation
Language of Document : English
Record Number : 151226
Doc. No : ET23018
Main Entry : Joseph V. Fasulo
Title Proper : Estimation of Internet Transit Times Using a Fast-Computing Artificial Neural Network (FC-ANN)
Note : This document is digital این مدرک بصورت الکترونیکی می باشد
Abstract : The objective of this research is to determine the macroscopic behavior of packettransit-times across the global Internet cloud us-hg an artificial neural network (ANN).Specifically, the problem addressed here refers to using a "fast-convergent" ANN for thepurpose indicated. The underlying principle of fast-convergence is that, the datapresented in training and prediction modes of the ANN is in the entropy (information-theoretic) domain, and the associated annealing process is "tuned" to adopt only theusehl information content and discard the posennopy part of the data presented.To demonstrate the efficacy of the research pursued, a feedforward ANN structureis developed and the necessary transformations required to convert the input data fromthe parametric-domain to the entropy-domain (and a corresponding inversetransformation) are followed so as to retrieve the output in parametric-domain.-....,....-...,..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 : TL46247.pdf
Title and statement of responsibility and : Estimation of Internet Transit Times Using a Fast-Computing Artificial Neural Network (FC-ANN) [Thesis]
 
 
 
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