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A Framework for Embedded Hypercube Interconnection Networks: Based on Neural Network Approach

by Mohd. Kalamuddin Ahmad, Mohd. Husain, A.a. Zilli
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 120 - Number 2
Year of Publication: 2015
Authors: Mohd. Kalamuddin Ahmad, Mohd. Husain, A.a. Zilli
10.5120/21201-3873

Mohd. Kalamuddin Ahmad, Mohd. Husain, A.a. Zilli . A Framework for Embedded Hypercube Interconnection Networks: Based on Neural Network Approach. International Journal of Computer Applications. 120, 2 ( June 2015), 25-34. DOI=10.5120/21201-3873

@article{ 10.5120/21201-3873,
author = { Mohd. Kalamuddin Ahmad, Mohd. Husain, A.a. Zilli },
title = { A Framework for Embedded Hypercube Interconnection Networks: Based on Neural Network Approach },
journal = { International Journal of Computer Applications },
issue_date = { June 2015 },
volume = { 120 },
number = { 2 },
month = { June },
year = { 2015 },
issn = { 0975-8887 },
pages = { 25-34 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume120/number2/21201-3873/ },
doi = { 10.5120/21201-3873 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:05:12.669598+05:30
%A Mohd. Kalamuddin Ahmad
%A Mohd. Husain
%A A.a. Zilli
%T A Framework for Embedded Hypercube Interconnection Networks: Based on Neural Network Approach
%J International Journal of Computer Applications
%@ 0975-8887
%V 120
%N 2
%P 25-34
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

This paper is concerned with routing of data in an embedded hypercube interconnection using the approach based on neural net architecture. To present a framework of the interconnection network consist number of nodes and number of connections. In this paper we first show that n dimensional hypercube can be embedded in layer neural layer network such that for any node of hypercube, its neighboring nodes of other layer are evenly partition into layers where each layer shares a manipulating or resulting data of different layers. Under this embedding network to fixed target and varying data input to produce output of the two incidence matrix of k-ary n-cube network to embedded in architecture.

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Index Terms

Computer Science
Information Sciences

Keywords

Hypercube network Parameters Embedded network Layered network Mean square error Performance Validation Scalability MIPS Neurons.

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