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"
Estimation of Internet Transit Times Using a Fast-Computing Artificial Neural Network (FC-ANN)
"
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]
http://localhost/site/catalogue/151226
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TL46247.pdf
TL46247.pdf
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